diff --git a/doc/LectureNotes/_build/.doctrees/environment.pickle b/doc/LectureNotes/_build/.doctrees/environment.pickle index de83812d4..ccd28e62d 100644 Binary files a/doc/LectureNotes/_build/.doctrees/environment.pickle and b/doc/LectureNotes/_build/.doctrees/environment.pickle differ diff --git a/doc/LectureNotes/_build/.doctrees/exercisesweek39.doctree b/doc/LectureNotes/_build/.doctrees/exercisesweek39.doctree index fedf7147c..f3cff541e 100644 Binary files a/doc/LectureNotes/_build/.doctrees/exercisesweek39.doctree and b/doc/LectureNotes/_build/.doctrees/exercisesweek39.doctree differ diff --git a/doc/LectureNotes/_build/html/_sources/exercisesweek39.ipynb b/doc/LectureNotes/_build/html/_sources/exercisesweek39.ipynb index 9805836c4..7e520c96d 100644 --- a/doc/LectureNotes/_build/html/_sources/exercisesweek39.ipynb +++ b/doc/LectureNotes/_build/html/_sources/exercisesweek39.ipynb @@ -5,7 +5,7 @@ "id": "433db993", "metadata": {}, "source": [ - "# Weekly Exercises 6\n", + "# Exercises week 39\n", "\n", "## Getting started with project 1\n" ] @@ -64,9 +64,21 @@ "\n", "**d)** Read the general guideline for writing a report, which can be found at .\n", "\n", - "**e)** Look at the provided example of an earlier project, found at \n" + "**e)** Look at the provided example of an earlier project, found at \n" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "338b2ee1", + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "id": "ec36f4c3", @@ -136,7 +148,7 @@ "\n", "**d)** Add python files for functions, and a notebook to produce the figures in exercise 2, to the Code folder. Remember to use a seed for generating random data and for train-test splits.\n", "\n", - "**e)** Create a README file in the reposotory or project folder with\n", + "**e)** Create a README file in the repository or project folder with\n", "\n", "- the name of the group members\n", "- a short description of the project\n", @@ -162,8 +174,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.15" } }, "nbformat": 4, diff --git a/doc/LectureNotes/_build/html/chapter1.html b/doc/LectureNotes/_build/html/chapter1.html index 1d13d9208..75ed2f975 100644 --- a/doc/LectureNotes/_build/html/chapter1.html +++ b/doc/LectureNotes/_build/html/chapter1.html @@ -232,7 +232,7 @@
  • Exercises week 37
  • Week 37: Gradient descent methods
  • Exercises week 38
    • -
  • Weekly Exercises 6
    • +
  • Exercises week 39

    • Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

      @@ -646,7 +646,7 @@ show that

      title="next page">

      next

      -

      Weekly Exercises 6

      +

      Exercises week 39

      diff --git a/doc/LectureNotes/_build/html/exercisesweek39.html b/doc/LectureNotes/_build/html/exercisesweek39.html index e594716ed..850b3f56c 100644 --- a/doc/LectureNotes/_build/html/exercisesweek39.html +++ b/doc/LectureNotes/_build/html/exercisesweek39.html @@ -8,7 +8,7 @@ - Weekly Exercises 6 — Applied Data Analysis and Machine Learning + Exercises week 39 — Applied Data Analysis and Machine Learning @@ -230,7 +230,7 @@
    • Exercises week 37
    • Week 37: Gradient descent methods
    • Exercises week 38
      • -
    • Weekly Exercises 6
      • +
    • Exercises week 39

    Projects

      @@ -373,7 +373,7 @@ document.write(`
      -

      Weekly Exercises 6

      +

      Exercises week 39

      @@ -404,8 +404,8 @@ document.write(`
      -
      -

      Weekly Exercises 6#

      +
      +

      Exercises week 39#

      Getting started with project 1#

      The aim of the exercises this week is to aid you in getting started with writing the report. This will be discussed during the lab sessions as well.

      @@ -435,7 +435,7 @@ document.write(`

      b) Download this template project.

      c) Create a new Overleaf project with the correct formatting by uploading the template project.

      d) Read the general guideline for writing a report, which can be found at CompPhysics/MachineLearning.

      -

      e) Look at the provided example of an earlier project, found at CompPhysics/MachineLearning

      +

      e) Look at the provided example of an earlier project, found at CompPhysics/MachineLearning

      Exercise 2: Adding good figures#

      @@ -459,7 +459,7 @@ document.write(`

      b) Add a PDF of the report to this repository, after completing exercises 1-3

      c) Add a folder named Code, where you can put python files for your functions and notebooks for reproducing your results.

      d) Add python files for functions, and a notebook to produce the figures in exercise 2, to the Code folder. Remember to use a seed for generating random data and for train-test splits.

      -

      e) Create a README file in the reposotory or project folder with

      +

      e) Create a README file in the repository or project folder with

      Projects

      Projects

      Projects

        diff --git a/doc/LectureNotes/_build/html/objects.inv b/doc/LectureNotes/_build/html/objects.inv index c42bd3331..d3198ebc0 100644 Binary files a/doc/LectureNotes/_build/html/objects.inv and b/doc/LectureNotes/_build/html/objects.inv differ diff --git a/doc/LectureNotes/_build/html/project1.html b/doc/LectureNotes/_build/html/project1.html index 2da5181be..2c2378fde 100644 --- a/doc/LectureNotes/_build/html/project1.html +++ b/doc/LectureNotes/_build/html/project1.html @@ -62,7 +62,7 @@ - + @@ -231,7 +231,7 @@
      • Exercises week 37
      • Week 37: Gradient descent methods
      • Exercises week 38
        • -
      • Weekly Exercises 6
        • +
      • Exercises week 39

      Projects

        @@ -758,7 +758,7 @@ of code developers and contributors keeps increasing.

        previous

        -

        Weekly Exercises 6

        +

        Exercises week 39

      diff --git a/doc/LectureNotes/_build/html/schedule.html b/doc/LectureNotes/_build/html/schedule.html index 79b50eae5..33022eed6 100644 --- a/doc/LectureNotes/_build/html/schedule.html +++ b/doc/LectureNotes/_build/html/schedule.html @@ -230,7 +230,7 @@
    • Exercises week 37
    • Week 37: Gradient descent methods
    • Exercises week 38
      • -
    • Weekly Exercises 6
      • +
    • Exercises week 39

    Projects

    Projects

      diff --git a/doc/LectureNotes/_build/html/searchindex.js b/doc/LectureNotes/_build/html/searchindex.js index 8ca1bd616..09eb41c3e 100644 --- a/doc/LectureNotes/_build/html/searchindex.js +++ b/doc/LectureNotes/_build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"1a)": [[18, "a"]], "3a)": [[18, "id1"]], "3b)": [[18, "b"]], "4a)": [[18, "id2"]], "4b)": [[18, "id3"]], "A Classification Tree": [[9, "a-classification-tree"]], "A Frequentist approach to data analysis": [[0, "a-frequentist-approach-to-data-analysis"], [28, "a-frequentist-approach-to-data-analysis"]], "A better approach": [[8, "a-better-approach"]], "A first summary": [[28, "a-first-summary"]], "A quick Reminder on Lagrangian Multipliers": [[8, "a-quick-reminder-on-lagrangian-multipliers"]], "A simple example": [[4, "a-simple-example"]], "A soft classifier": [[8, "a-soft-classifier"]], "A top-down perspective on Neural networks": [[1, "a-top-down-perspective-on-neural-networks"]], "ADAM algorithm, taken from Goodfellow et al": [[31, "adam-algorithm-taken-from-goodfellow-et-al"]], "ADAM optimizer": [[13, "adam-optimizer"], [31, "id2"]], "Accuracy": [[31, "accuracy"]], "Activation functions": [[12, "activation-functions"]], "AdaGrad Properties": [[31, "adagrad-properties"]], "AdaGrad Update Rule Derivation": [[31, "adagrad-update-rule-derivation"]], "AdaGrad algorithm, taken from Goodfellow et al": [[31, "adagrad-algorithm-taken-from-goodfellow-et-al"]], "Adam Optimizer": [[31, "adam-optimizer"]], "Adam vs. AdaGrad and RMSProp": [[31, "adam-vs-adagrad-and-rmsprop"]], "Adam: Bias Correction": [[31, "adam-bias-correction"]], "Adam: Exponential Moving Averages (Moments)": [[31, "adam-exponential-moving-averages-moments"]], "Adam: Update Rule Derivation": [[31, "adam-update-rule-derivation"]], "Adaptive boosting: AdaBoost, Basic Algorithm": [[10, "adaptive-boosting-adaboost-basic-algorithm"]], "Adaptivity Across Dimensions": [[31, "adaptivity-across-dimensions"]], "Adding error analysis and training set up": [[28, "adding-error-analysis-and-training-set-up"], [29, "adding-error-analysis-and-training-set-up"]], "Adjust hyperparameters": [[1, "adjust-hyperparameters"]], "Algorithms and codes for Adagrad, RMSprop and Adam": [[31, "algorithms-and-codes-for-adagrad-rmsprop-and-adam"]], "Algorithms for Setting up Decision Trees": [[9, "algorithms-for-setting-up-decision-trees"]], "An Overview of Ensemble Methods": [[10, "an-overview-of-ensemble-methods"]], "An extrapolation example": [[4, "an-extrapolation-example"]], "An optimization/minimization problem": [[28, "an-optimization-minimization-problem"]], "And finally \\boldsymbol{X}\\boldsymbol{X}^T": [[29, "and-finally-boldsymbol-x-boldsymbol-x-t"]], "And finally ADAM": [[31, "and-finally-adam"]], "And what about using neural networks?": [[28, "and-what-about-using-neural-networks"]], "Another Example, now with a polynomial fit": [[30, "another-example-now-with-a-polynomial-fit"]], "Another example, the moons again": [[9, "another-example-the-moons-again"]], "Applied Data Analysis and Machine Learning": [[21, null]], "Autocorrelation function": [[25, "autocorrelation-function"]], "Automatic differentiation": [[13, "automatic-differentiation"]], "Back to Ridge and LASSO Regression": [[29, "back-to-ridge-and-lasso-regression"], [30, "back-to-ridge-and-lasso-regression"]], "Back to the Cancer Data": [[11, "back-to-the-cancer-data"]], "Background literature": [[23, "background-literature"]], "Bagging": [[10, "bagging"]], "Bagging Examples": [[10, "bagging-examples"]], "Basic Matrix Features": [[22, "basic-matrix-features"]], "Basic ideas of the Principal Component Analysis (PCA)": [[11, null]], "Basic math of the SVD": [[5, "basic-math-of-the-svd"], [29, "basic-math-of-the-svd"], [30, "basic-math-of-the-svd"]], "Basics": [[7, "basics"]], "Basics of a tree": [[9, "basics-of-a-tree"]], "Batch Normalization": [[1, "batch-normalization"]], "Batches and mini-batches": [[31, "batches-and-mini-batches"]], "Bayes\u2019 Theorem and Ridge and Lasso Regression": [[5, "bayes-theorem-and-ridge-and-lasso-regression"]], "Boosting, a Bird\u2019s Eye View": [[10, "boosting-a-bird-s-eye-view"]], "Bootstrap": [[6, "bootstrap"]], "Bringing it together, first back propagation equation": [[12, "bringing-it-together-first-back-propagation-equation"]], "Building a Feed Forward Neural Network": [[1, null]], "Building a tree, regression": [[9, "building-a-tree-regression"]], "Building neural networks in Tensorflow and Keras": [[1, "building-neural-networks-in-tensorflow-and-keras"]], "But none of these can compete with Newton\u2019s method": [[31, "but-none-of-these-can-compete-with-newton-s-method"]], "CNNs in more detail, building convolutional neural networks in Tensorflow and Keras": [[3, "cnns-in-more-detail-building-convolutional-neural-networks-in-tensorflow-and-keras"]], "Cancer Data again now with Decision Trees and other Methods": [[9, "cancer-data-again-now-with-decision-trees-and-other-methods"]], "Challenge: Choosing a Fixed Learning Rate": [[31, "challenge-choosing-a-fixed-learning-rate"]], "Choose cost function and optimizer": [[1, "choose-cost-function-and-optimizer"]], "Classical PCA Theorem": [[11, "classical-pca-theorem"]], "Clustering and Unsupervised Learning": [[14, null]], "Code for SVD and Inversion of Matrices": [[5, "code-for-svd-and-inversion-of-matrices"]], "Code with a Number of Minibatches which varies": [[31, "code-with-a-number-of-minibatches-which-varies"]], "Codes and Approaches": [[14, "codes-and-approaches"]], "Codes for the SVD": [[5, "codes-for-the-svd"], [29, "codes-for-the-svd"], [30, "codes-for-the-svd"]], "Coding Setup and Linear Regression": [[15, "coding-setup-and-linear-regression"]], "Collect and pre-process data": [[1, "collect-and-pre-process-data"]], "Communication channels": [[28, "communication-channels"]], "Compare Bagging on Trees with Random Forests": [[10, "compare-bagging-on-trees-with-random-forests"]], "Comparing with a numerical scheme": [[2, "comparing-with-a-numerical-scheme"]], "Comparison with OLS": [[30, "comparison-with-ols"]], "Computation of gradients": [[31, "computation-of-gradients"]], "Computing the Gini index": [[9, "computing-the-gini-index"]], "Conditions on convex functions": [[30, "conditions-on-convex-functions"]], "Conjugate gradient method": [[13, "conjugate-gradient-method"]], "Convergence rates": [[31, "convergence-rates"]], "Convex function": [[30, "convex-function"]], "Convex functions": [[13, "convex-functions"], [30, "convex-functions"]], "Convolution Examples: Polynomial multiplication": [[3, "convolution-examples-polynomial-multiplication"]], "Convolution Examples: Principle of Superposition and Periodic Forces (Fourier Transforms)": [[3, "convolution-examples-principle-of-superposition-and-periodic-forces-fourier-transforms"]], "Convolutional Neural Network": [[12, "convolutional-neural-network"]], "Convolutional Neural Networks": [[3, null]], "Correlation Function and Design/Feature Matrix": [[29, "correlation-function-and-design-feature-matrix"]], "Correlation Matrix": [[11, "correlation-matrix"], [29, "correlation-matrix"]], "Correlation Matrix with Pandas": [[29, "correlation-matrix-with-pandas"]], "Course Format": [[28, "course-format"]], "Course setting": [[24, null]], "Covariance Matrix Examples": [[29, "covariance-matrix-examples"]], "Covariance and Correlation Matrix": [[29, "covariance-and-correlation-matrix"]], "Cross-validation": [[6, "cross-validation"]], "Deadlines for projects (tentative)": [[28, "deadlines-for-projects-tentative"]], "Decision trees, overarching aims": [[9, null]], "Deep Neural Networks": [[31, "deep-neural-networks"]], "Deep learning methods": [[28, "deep-learning-methods"]], "Define model and architecture": [[1, "define-model-and-architecture"]], "Defining the cost function": [[1, "defining-the-cost-function"]], "Definitions": [[19, "definitions"]], "Deliverables": [[15, "deliverables"], [16, "deliverables"], [19, "deliverables"], [20, "deliverables"]], "Derivation of the AdaGrad Algorithm": [[31, "derivation-of-the-adagrad-algorithm"]], "Derivatives and the chain rule": [[12, "derivatives-and-the-chain-rule"]], "Derivatives, example 1": [[29, "derivatives-example-1"]], "Deriving OLS from a probability distribution": [[5, "deriving-ols-from-a-probability-distribution"]], "Deriving and Implementing Ordinary Least Squares": [[16, "deriving-and-implementing-ordinary-least-squares"]], "Deriving and Implementing Ridge Regression": [[17, "deriving-and-implementing-ridge-regression"]], "Deriving the Lasso Regression Equations": [[29, "deriving-the-lasso-regression-equations"], [30, "deriving-the-lasso-regression-equations"], [30, "id6"]], "Deriving the Ridge Regression Equations": [[29, "deriving-the-ridge-regression-equations"], [30, "deriving-the-ridge-regression-equations"], [30, "id3"]], "Deriving the back propagation code for a multilayer perceptron model": [[12, "deriving-the-back-propagation-code-for-a-multilayer-perceptron-model"]], "Developing a code for doing neural networks with back propagation": [[1, "developing-a-code-for-doing-neural-networks-with-back-propagation"]], "Diagonalize the sample covariance matrix to obtain the principal components": [[11, "diagonalize-the-sample-covariance-matrix-to-obtain-the-principal-components"]], "Different kernels and Mercer\u2019s theorem": [[8, "different-kernels-and-mercer-s-theorem"]], "Disadvantages": [[9, "disadvantages"]], "Discriminative Modeling": [[28, "discriminative-modeling"]], "Domains and probabilities": [[25, "domains-and-probabilities"]], "Dropout": [[1, "dropout"]], "Economy-size SVD": [[29, "economy-size-svd"], [30, "economy-size-svd"]], "Elements of Probability Theory and Statistical Data Analysis": [[25, null]], "Empirical Evidence: Convergence Time and Memory in Practice": [[31, "empirical-evidence-convergence-time-and-memory-in-practice"]], "Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods": [[10, null]], "Entropy and the ID3 algorithm": [[9, "entropy-and-the-id3-algorithm"]], "Essential elements of ML": [[28, "essential-elements-of-ml"]], "Evaluate model performance on test data": [[1, "evaluate-model-performance-on-test-data"]], "Example 2": [[29, "example-2"]], "Example 3": [[29, "example-3"]], "Example 4": [[29, "example-4"]], "Example Matrix": [[29, "example-matrix"], [30, "example-matrix"]], "Example of discriminative modeling, taken from Generative Deep Learning by David Foster": [[28, "example-of-discriminative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of generative modeling, taken from Generative Deep Learning by David Foster": [[28, "example-of-generative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of own Standard scaling": [[29, "example-of-own-standard-scaling"]], "Example relevant for the exercises": [[29, "example-relevant-for-the-exercises"]], "Example: Exponential decay": [[2, "example-exponential-decay"]], "Example: Population growth": [[2, "example-population-growth"]], "Example: The diffusion equation": [[2, "example-the-diffusion-equation"]], "Example: binary classification problem": [[1, "example-binary-classification-problem"]], "Examples": [[28, "examples"]], "Examples of likelihood functions used in logistic regression and neural networks": [[7, "examples-of-likelihood-functions-used-in-logistic-regression-and-neural-networks"]], "Exercise 1 - Choice of model and degrees of freedom": [[17, "exercise-1-choice-of-model-and-degrees-of-freedom"]], "Exercise 1 - Finding the derivative of Matrix-Vector expressions": [[16, "exercise-1-finding-the-derivative-of-matrix-vector-expressions"]], "Exercise 1 - Github Setup": [[15, "exercise-1-github-setup"]], "Exercise 1, scale your data": [[18, "exercise-1-scale-your-data"]], "Exercise 1: Creating the report document": [[20, "exercise-1-creating-the-report-document"]], "Exercise 1: Expectation values for ordinary least squares expressions": [[19, "exercise-1-expectation-values-for-ordinary-least-squares-expressions"]], "Exercise 1: Setting up various Python environments": [[0, "exercise-1-setting-up-various-python-environments"]], "Exercise 2 - Deriving the expression for OLS": [[16, "exercise-2-deriving-the-expression-for-ols"]], "Exercise 2 - Deriving the expression for Ridge Regression": [[17, "exercise-2-deriving-the-expression-for-ridge-regression"]], "Exercise 2 - Setting up a Github repository": [[15, "exercise-2-setting-up-a-github-repository"]], "Exercise 2, calculate the gradients": [[18, "exercise-2-calculate-the-gradients"]], "Exercise 2: Adding good figures": [[20, "exercise-2-adding-good-figures"]], "Exercise 2: Expectation values for Ridge regression": [[19, "exercise-2-expectation-values-for-ridge-regression"]], "Exercise 2: making your own data and exploring scikit-learn": [[0, "exercise-2-making-your-own-data-and-exploring-scikit-learn"]], "Exercise 3 - Creating feature matrix and implementing OLS using the analytical expression": [[16, "exercise-3-creating-feature-matrix-and-implementing-ols-using-the-analytical-expression"]], "Exercise 3 - Fitting an OLS model to data": [[15, "exercise-3-fitting-an-ols-model-to-data"]], "Exercise 3 - Scaling data": [[17, "exercise-3-scaling-data"]], "Exercise 3 - Setting up a Python virtual environment": [[15, "exercise-3-setting-up-a-python-virtual-environment"]], "Exercise 3, using the analytical formulae for OLS and Ridge regression to find the optimal paramters \\boldsymbol{\\theta}": [[18, "exercise-3-using-the-analytical-formulae-for-ols-and-ridge-regression-to-find-the-optimal-paramters-boldsymbol-theta"]], "Exercise 3: Deriving the expression for the Bias-Variance Trade-off": [[19, "exercise-3-deriving-the-expression-for-the-bias-variance-trade-off"]], "Exercise 3: Normalizing our data": [[0, "exercise-3-normalizing-our-data"]], "Exercise 3: Writing an abstract and introduction": [[20, "exercise-3-writing-an-abstract-and-introduction"]], "Exercise 4 - Fitting a polynomial": [[16, "exercise-4-fitting-a-polynomial"]], "Exercise 4 - Implementing Ridge Regression": [[17, "exercise-4-implementing-ridge-regression"]], "Exercise 4 - Testing multiple hyperparameters": [[17, "exercise-4-testing-multiple-hyperparameters"]], "Exercise 4 - The train-test split": [[15, "exercise-4-the-train-test-split"]], "Exercise 4, Implementing the simplest form for gradient descent": [[18, "exercise-4-implementing-the-simplest-form-for-gradient-descent"]], "Exercise 4: Adding Ridge Regression": [[0, "exercise-4-adding-ridge-regression"]], "Exercise 4: Computing the Bias and Variance": [[19, "exercise-4-computing-the-bias-and-variance"]], "Exercise 4: Making the code avaliable and presentable": [[20, "exercise-4-making-the-code-avaliable-and-presentable"]], "Exercise 5 - Comparing your code with sklearn": [[16, "exercise-5-comparing-your-code-with-sklearn"]], "Exercise 5, Ridge regression and a new Synthetic Dataset": [[18, "exercise-5-ridge-regression-and-a-new-synthetic-dataset"]], "Exercise 5: Analytical exercises": [[0, "exercise-5-analytical-exercises"]], "Exercise 5: Interpretation of scaling and metrics": [[19, "exercise-5-interpretation-of-scaling-and-metrics"]], "Exercise 5: Referencing": [[20, "exercise-5-referencing"]], "Exercise: Cross-validation as resampling techniques, adding more complexity": [[6, "exercise-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Exercise: Analysis of real data": [[6, "exercise-analysis-of-real-data"]], "Exercise: Bias-variance trade-off and resampling techniques": [[6, "exercise-bias-variance-trade-off-and-resampling-techniques"]], "Exercise: Lasso Regression on the Franke function with resampling": [[6, "exercise-lasso-regression-on-the-franke-function-with-resampling"]], "Exercise: Ordinary Least Square (OLS) on the Franke function": [[6, "exercise-ordinary-least-square-ols-on-the-franke-function"]], "Exercise: Ridge Regression on the Franke function with resampling": [[6, "exercise-ridge-regression-on-the-franke-function-with-resampling"]], "Exercises": [[0, "exercises"]], "Exercises and Projects": [[6, "exercises-and-projects"]], "Exercises week 34": [[15, null]], "Exercises week 35": [[16, null]], "Exercises week 36": [[17, null]], "Exercises week 37": [[18, null]], "Exercises week 38": [[19, null]], "Expectation values": [[25, "expectation-values"]], "Extending to more than one variable": [[30, "extending-to-more-than-one-variable"]], "Extremely useful tools, strongly recommended": [[28, "extremely-useful-tools-strongly-recommended"]], "Feed-forward neural networks": [[12, "feed-forward-neural-networks"]], "Feed-forward pass": [[1, "feed-forward-pass"]], "Final back propagating equation": [[12, "final-back-propagating-equation"]], "Fine-tuning neural network hyperparameters": [[1, "fine-tuning-neural-network-hyperparameters"]], "Fitting an Equation of State for Dense Nuclear Matter": [[0, "fitting-an-equation-of-state-for-dense-nuclear-matter"]], "Fixing the singularity": [[29, "fixing-the-singularity"], [30, "fixing-the-singularity"]], "Format for electronic delivery of report and programs": [[23, "format-for-electronic-delivery-of-report-and-programs"]], "Frequently used scaling functions": [[29, "frequently-used-scaling-functions"], [31, "frequently-used-scaling-functions"]], "From OLS to Ridge and Lasso": [[30, "from-ols-to-ridge-and-lasso"]], "From one to many layers, the universal approximation theorem": [[12, "from-one-to-many-layers-the-universal-approximation-theorem"]], "Functionality in Scikit-Learn": [[29, "functionality-in-scikit-learn"], [31, "functionality-in-scikit-learn"]], "Further Dimensionality Remarks": [[3, "further-dimensionality-remarks"]], "Further properties (important for our analyses later)": [[5, "further-properties-important-for-our-analyses-later"], [29, "further-properties-important-for-our-analyses-later"], [30, "further-properties-important-for-our-analyses-later"]], "Gaussian Elimination": [[22, "gaussian-elimination"]], "General Features": [[9, "general-features"]], "General linear models and linear algebra": [[28, "general-linear-models-and-linear-algebra"]], "Generalizing the fitting procedure as a linear algebra problem": [[28, "generalizing-the-fitting-procedure-as-a-linear-algebra-problem"], [28, "id1"]], "Generative Adversarial Networks": [[4, "generative-adversarial-networks"]], "Generative Models": [[4, "generative-models"]], "Generative Versus Discriminative Modeling": [[28, "generative-versus-discriminative-modeling"]], "Geometric Interpretation and link with Singular Value Decomposition": [[11, "geometric-interpretation-and-link-with-singular-value-decomposition"]], "Getting started with project 1": [[20, "getting-started-with-project-1"]], "Gradient Boosting, Classification Example": [[10, "gradient-boosting-classification-example"]], "Gradient Boosting, Examples of Regression": [[10, "gradient-boosting-examples-of-regression"]], "Gradient Clipping": [[1, "gradient-clipping"]], "Gradient Descent Example": [[30, "id1"], [31, "id1"]], "Gradient boosting: Basics with Steepest Descent/Functional Gradient Descent": [[10, "gradient-boosting-basics-with-steepest-descent-functional-gradient-descent"]], "Gradient descent": [[2, "gradient-descent"]], "Gradient descent and Ridge": [[30, "gradient-descent-and-ridge"], [31, "gradient-descent-and-ridge"]], "Gradient descent and revisiting Ordinary Least Squares from last week": [[31, "gradient-descent-and-revisiting-ordinary-least-squares-from-last-week"]], "Gradient descent example": [[30, "gradient-descent-example"], [31, "gradient-descent-example"]], "Grading": [[26, "grading"], [26, "id2"], [28, "grading"]], "How to take derivatives of Matrix-Vector expressions": [[16, "how-to-take-derivatives-of-matrix-vector-expressions"]], "Hyperplanes and all that": [[8, "hyperplanes-and-all-that"]], "Important Matrix and vector handling packages": [[22, "important-matrix-and-vector-handling-packages"]], "Important technicalities: More on Rescaling data": [[29, "important-technicalities-more-on-rescaling-data"]], "Improving gradient descent with momentum": [[31, "improving-gradient-descent-with-momentum"]], "Improving performance": [[1, "improving-performance"]], "In summary": [[26, "in-summary"]], "Including Stochastic Gradient Descent with Autograd": [[13, "including-stochastic-gradient-descent-with-autograd"], [31, "including-stochastic-gradient-descent-with-autograd"]], "Incremental PCA": [[11, "incremental-pca"]], "Installing R, C++, cython or Julia": [[28, "installing-r-c-cython-or-julia"]], "Installing R, C++, cython, Numba etc": [[28, "installing-r-c-cython-numba-etc"]], "Instructor information": [[26, "instructor-information"]], "Interpretations and optimizing our parameters": [[28, "interpretations-and-optimizing-our-parameters"], [28, "id2"], [28, "id3"], [29, "interpretations-and-optimizing-our-parameters"], [29, "id1"], [29, "id2"]], "Interpreting the Ridge results": [[29, "interpreting-the-ridge-results"], [30, "interpreting-the-ridge-results"], [30, "id4"]], "Introducing JAX": [[13, "introducing-jax"]], "Introducing the Covariance and Correlation functions": [[11, "introducing-the-covariance-and-correlation-functions"], [29, "introducing-the-covariance-and-correlation-functions"]], "Introduction": [[0, "introduction"], [6, "introduction"], [21, "introduction"], [22, "introduction"]], "Introduction to numerical projects": [[23, "introduction-to-numerical-projects"]], "Iterative Fitting, Classification and AdaBoost": [[10, "iterative-fitting-classification-and-adaboost"]], "Iterative Fitting, Regression and Squared-error Cost Function": [[10, "iterative-fitting-regression-and-squared-error-cost-function"]], "Kernel PCA": [[11, "kernel-pca"]], "Kernels and non-linearity": [[8, "kernels-and-non-linearity"]], "LU Decomposition, the inverse of a matrix": [[22, "lu-decomposition-the-inverse-of-a-matrix"]], "Lasso Regression": [[30, "lasso-regression"]], "Lasso case": [[30, "lasso-case"]], "Layers": [[1, "layers"]], "Layers used to build CNNs": [[3, "layers-used-to-build-cnns"]], "Learning goals": [[15, "learning-goals"], [16, "learning-goals"], [17, "learning-goals"], [18, "learning-goals"], [19, "learning-goals"], [20, "learning-goals"]], "Learning outcomes": [[21, "learning-outcomes"], [28, "learning-outcomes"]], "Lectures and ComputerLab": [[28, "lectures-and-computerlab"]], "Limitations of supervised learning with deep networks": [[1, "limitations-of-supervised-learning-with-deep-networks"]], "Linear Algebra, Handling of Arrays and more Python Features": [[22, null]], "Linear Regression": [[0, null]], "Linear Regression Problems": [[29, "linear-regression-problems"], [30, "linear-regression-problems"]], "Linear Regression and the SVD": [[30, "linear-regression-and-the-svd"]], "Linear Regression, basic elements": [[0, "linear-regression-basic-elements"]], "Linking Bayes\u2019 Theorem with Ridge and Lasso Regression": [[5, "linking-bayes-theorem-with-ridge-and-lasso-regression"]], "Linking the regression analysis with a statistical interpretation": [[5, "linking-the-regression-analysis-with-a-statistical-interpretation"]], "Linking with the SVD": [[5, "linking-with-the-svd"], [29, "linking-with-the-svd"]], "Links to relevant courses at the University of Oslo": [[27, "links-to-relevant-courses-at-the-university-of-oslo"]], "Logistic Regression": [[7, null], [7, "id1"]], "MNIST and GANs": [[4, "mnist-and-gans"]], "Machine Learning": [[28, "machine-learning"]], "Machine learning": [[21, "machine-learning"]], "Main textbooks": [[28, "main-textbooks"]], "Making a tree": [[9, "making-a-tree"]], "Making your own Bootstrap: Changing the Level of the Decision Tree": [[10, "making-your-own-bootstrap-changing-the-level-of-the-decision-tree"]], "Making your own test-train splitting": [[29, "making-your-own-test-train-splitting"]], "Material for exercises week 35": [[29, "material-for-exercises-week-35"]], "Material for lab sessions sessions Tuesday and Wednesday": [[30, "material-for-lab-sessions-sessions-tuesday-and-wednesday"]], "Material for lecture Monday September 2": [[30, "material-for-lecture-monday-september-2"]], "Material for lecture Monday September 8": [[31, "material-for-lecture-monday-september-8"]], "Material for the lab sessions": [[31, "material-for-the-lab-sessions"]], "Mathematical Interpretation of Ordinary Least Squares": [[5, "mathematical-interpretation-of-ordinary-least-squares"], [29, "mathematical-interpretation-of-ordinary-least-squares"], [30, "mathematical-interpretation-of-ordinary-least-squares"]], "Mathematical optimization of convex functions": [[8, "mathematical-optimization-of-convex-functions"]], "Mathematics of CNNs": [[3, "mathematics-of-cnns"]], "Mathematics of the SVD and implications": [[5, "mathematics-of-the-svd-and-implications"], [29, "mathematics-of-the-svd-and-implications"], [30, "mathematics-of-the-svd-and-implications"]], "Matrices in Python": [[28, "matrices-in-python"]], "Matrix multiplication": [[1, "matrix-multiplication"]], "Matrix-vector notation and activation": [[12, "matrix-vector-notation-and-activation"]], "Meet the covariance!": [[25, "meet-the-covariance"]], "Meet the Covariance Matrix": [[5, "meet-the-covariance-matrix"], [29, "meet-the-covariance-matrix"]], "Meet the Hessian Matrix": [[29, "meet-the-hessian-matrix"]], "Meet the Pandas": [[28, "meet-the-pandas"]], "Memory Usage and Scalability": [[31, "memory-usage-and-scalability"]], "Memory constraints": [[31, "memory-constraints"]], "Min-Max Scaling": [[29, "min-max-scaling"]], "Momentum based GD": [[13, "momentum-based-gd"], [31, "momentum-based-gd"]], "More complicated Example: The Ising model": [[6, "more-complicated-example-the-ising-model"]], "More interpretations": [[29, "more-interpretations"], [30, "more-interpretations"], [30, "id5"]], "More on Dimensionalities": [[3, "more-on-dimensionalities"]], "More on Rescaling data": [[6, "more-on-rescaling-data"]], "More on Steepest descent": [[30, "more-on-steepest-descent"]], "More on convex functions": [[30, "more-on-convex-functions"]], "More preprocessing": [[29, "more-preprocessing"], [31, "more-preprocessing"]], "Motivation for Adaptive Step Sizes": [[31, "motivation-for-adaptive-step-sizes"]], "Multilayer perceptrons": [[12, "multilayer-perceptrons"]], "Network requirements": [[2, "network-requirements"]], "Neural Networks vs CNNs": [[3, "neural-networks-vs-cnns"]], "Neural networks": [[12, null]], "Non-Convex Problems": [[31, "non-convex-problems"]], "Note about SVD Calculations": [[29, "note-about-svd-calculations"], [30, "note-about-svd-calculations"]], "Note on Scikit-Learn": [[30, "note-on-scikit-learn"]], "Numerical experiments and the covariance, central limit theorem": [[25, "numerical-experiments-and-the-covariance-central-limit-theorem"]], "Numpy and arrays": [[22, "numpy-and-arrays"], [28, "numpy-and-arrays"]], "Numpy examples and Important Matrix and vector handling packages": [[28, "numpy-examples-and-important-matrix-and-vector-handling-packages"]], "Optimization and gradient descent, the central part of any Machine Learning algortithm": [[30, "optimization-and-gradient-descent-the-central-part-of-any-machine-learning-algortithm"]], "Optimization, the central part of any Machine Learning algortithm": [[13, null]], "Optimizing our parameters": [[28, "optimizing-our-parameters"]], "Optimizing our parameters, more details": [[28, "optimizing-our-parameters-more-details"]], "Optimizing the cost function": [[1, "optimizing-the-cost-function"]], "Organizing our data": [[0, "organizing-our-data"], [28, "organizing-our-data"]], "Other Matrix and Vector Operations": [[22, "other-matrix-and-vector-operations"]], "Other Types of Recurrent Neural Networks": [[4, "other-types-of-recurrent-neural-networks"]], "Other courses on Data science and Machine Learning at UiO": [[28, "other-courses-on-data-science-and-machine-learning-at-uio"]], "Other courses on Data science and Machine Learning at UiO, contn": [[28, "other-courses-on-data-science-and-machine-learning-at-uio-contn"]], "Other popular texts": [[28, "other-popular-texts"]], "Other techniques": [[11, "other-techniques"]], "Other types of networks": [[12, "other-types-of-networks"]], "Other ways of visualizing the trees": [[9, "other-ways-of-visualizing-the-trees"]], "Our model for the nuclear binding energies": [[28, "our-model-for-the-nuclear-binding-energies"]], "Overview of first week": [[28, "overview-of-first-week"]], "Overview video on Stochastic Gradient Descent (SGD)": [[31, "overview-video-on-stochastic-gradient-descent-sgd"]], "Own code for Ordinary Least Squares": [[28, "own-code-for-ordinary-least-squares"], [29, "own-code-for-ordinary-least-squares"]], "PCA and scikit-learn": [[11, "pca-and-scikit-learn"]], "Pandas AI": [[28, "pandas-ai"]], "Part a : Ordinary Least Square (OLS) for the Runge function": [[23, "part-a-ordinary-least-square-ols-for-the-runge-function"]], "Part b: Adding Ridge regression for the Runge function": [[23, "part-b-adding-ridge-regression-for-the-runge-function"]], "Part c: Writing your own gradient descent code": [[23, "part-c-writing-your-own-gradient-descent-code"]], "Part d: Including momentum and more advanced ways to update the learning the rate": [[23, "part-d-including-momentum-and-more-advanced-ways-to-update-the-learning-the-rate"]], "Part e: Writing our own code for Lasso regression": [[23, "part-e-writing-our-own-code-for-lasso-regression"]], "Part f: Stochastic gradient descent": [[23, "part-f-stochastic-gradient-descent"]], "Part g: Bias-variance trade-off and resampling techniques": [[23, "part-g-bias-variance-trade-off-and-resampling-techniques"]], "Part h): Cross-validation as resampling techniques, adding more complexity": [[23, "part-h-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Partial Differential Equations": [[2, "partial-differential-equations"]], "Plans for week 35": [[29, "plans-for-week-35"]], "Plans for week 36": [[30, "plans-for-week-36"]], "Plans for week 37, lecture Monday": [[31, "plans-for-week-37-lecture-monday"]], "Practical tips": [[13, "practical-tips"], [31, "practical-tips"]], "Practicalities": [[26, "practicalities"], [26, "id1"]], "Preamble: Note on writing reports, using reference material, AI and other tools": [[23, "preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools"]], "Predicting New Points With A Trained Recurrent Neural Network": [[4, "predicting-new-points-with-a-trained-recurrent-neural-network"]], "Preprocessing our data": [[29, "preprocessing-our-data"]], "Prerequisites": [[28, "prerequisites"]], "Prerequisites and background": [[21, "prerequisites-and-background"]], "Prerequisites: Collect and pre-process data": [[3, "prerequisites-collect-and-pre-process-data"]], "Probability Distribution Functions": [[25, "probability-distribution-functions"]], "Program example for gradient descent with Ridge Regression": [[30, "program-example-for-gradient-descent-with-ridge-regression"], [31, "program-example-for-gradient-descent-with-ridge-regression"]], "Program for stochastic gradient": [[13, "program-for-stochastic-gradient"]], "Project 1 on Machine Learning, deadline October 6 (midnight), 2025": [[23, null]], "Properties of PDFs": [[25, "properties-of-pdfs"]], "Pros and cons": [[31, "pros-and-cons"]], "Pros and cons of trees, pros": [[9, "pros-and-cons-of-trees-pros"]], "Python installers": [[21, "python-installers"], [28, "python-installers"]], "RMS prop": [[13, "rms-prop"]], "RMSProp algorithm, taken from Goodfellow et al": [[31, "rmsprop-algorithm-taken-from-goodfellow-et-al"]], "RMSProp: Adaptive Learning Rates": [[31, "rmsprop-adaptive-learning-rates"]], "RMSprop for adaptive learning rate with Stochastic Gradient Descent": [[31, "rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent"]], "Random Numbers": [[25, "random-numbers"]], "Random forests": [[10, "random-forests"]], "Randomized PCA": [[11, "randomized-pca"]], "Reading material": [[28, "reading-material"]], "Reading recommendations:": [[29, "reading-recommendations"]], "Reading suggestions week 34": [[28, "reading-suggestions-week-34"]], "Readings and Videos:": [[31, "readings-and-videos"]], "Recurrent neural networks": [[12, "recurrent-neural-networks"]], "Recurrent neural networks: Overarching view": [[4, null]], "Reducing the number of degrees of freedom, overarching view": [[0, "reducing-the-number-of-degrees-of-freedom-overarching-view"], [29, "reducing-the-number-of-degrees-of-freedom-overarching-view"]], "Reformulating the problem": [[2, "reformulating-the-problem"]], "Regression Case": [[10, "regression-case"]], "Regression analysis and resampling methods": [[23, "regression-analysis-and-resampling-methods"]], "Regression analysis, overarching aims": [[28, "regression-analysis-overarching-aims"]], "Regression analysis, overarching aims II": [[28, "regression-analysis-overarching-aims-ii"]], "Regularization": [[1, "regularization"]], "Reminder from last week": [[29, "reminder-from-last-week"]], "Reminder on Newton-Raphson\u2019s method": [[30, "reminder-on-newton-raphson-s-method"]], "Reminder on Statistics": [[6, "reminder-on-statistics"]], "Reminder on different scaling methods": [[31, "reminder-on-different-scaling-methods"]], "Replace or not": [[13, "replace-or-not"], [31, "replace-or-not"]], "Required Technologies": [[21, "required-technologies"]], "Resampling Methods": [[6, null]], "Resampling and the Bias-Variance Trade-off": [[19, "resampling-and-the-bias-variance-trade-off"]], "Resampling methods": [[6, "id1"]], "Residual Error": [[29, "residual-error"], [30, "residual-error"]], "Resources on differential equations and deep learning": [[2, "resources-on-differential-equations-and-deep-learning"]], "Revisiting Ordinary Least Squares": [[30, "revisiting-ordinary-least-squares"]], "Revisiting our Linear Regression Solvers": [[13, "revisiting-our-linear-regression-solvers"]], "Rewriting the Covariance and/or Correlation Matrix": [[29, "rewriting-the-covariance-and-or-correlation-matrix"]], "Rewriting the fitting procedure as a linear algebra problem": [[28, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem"]], "Rewriting the fitting procedure as a linear algebra problem, more details": [[28, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem-more-details"]], "Ridge Regression": [[30, "ridge-regression"]], "Ridge and LASSO Regression": [[29, "ridge-and-lasso-regression"], [30, "ridge-and-lasso-regression"], [30, "id2"]], "Ridge and Lasso Regression": [[5, null], [5, "id1"]], "SGD example": [[31, "sgd-example"]], "SGD vs Full-Batch GD: Convergence Speed and Memory Comparison": [[31, "sgd-vs-full-batch-gd-convergence-speed-and-memory-comparison"]], "SVD analysis": [[30, "svd-analysis"]], "Same code but now with momentum gradient descent": [[13, "same-code-but-now-with-momentum-gradient-descent"], [31, "same-code-but-now-with-momentum-gradient-descent"], [31, "id3"], [31, "id4"]], "Schedule first week": [[28, "schedule-first-week"]], "Schematic Regression Procedure": [[9, "schematic-regression-procedure"]], "Second moment of the gradient": [[31, "second-moment-of-the-gradient"]], "September 15-19": [[19, "september-15-19"]], "Setting up the Back propagation algorithm": [[12, "setting-up-the-back-propagation-algorithm"]], "Setting up the Matrix to be inverted": [[29, "setting-up-the-matrix-to-be-inverted"], [30, "setting-up-the-matrix-to-be-inverted"]], "Setting up the network using Autograd; The full program": [[2, "setting-up-the-network-using-autograd-the-full-program"]], "Similar (second order function now) problem but now with AdaGrad": [[13, "similar-second-order-function-now-problem-but-now-with-adagrad"], [31, "similar-second-order-function-now-problem-but-now-with-adagrad"]], "Simple Python Code to read in Data and perform Classification": [[9, "simple-python-code-to-read-in-data-and-perform-classification"]], "Simple case": [[29, "simple-case"], [30, "simple-case"]], "Simple code for solving the above problem": [[30, "simple-code-for-solving-the-above-problem"]], "Simple example code": [[31, "simple-example-code"]], "Simple example to illustrate Ordinary Least Squares, Ridge and Lasso Regression": [[30, "simple-example-to-illustrate-ordinary-least-squares-ridge-and-lasso-regression"]], "Simple geometric interpretation": [[30, "simple-geometric-interpretation"]], "Simple linear regression model using scikit-learn": [[0, "simple-linear-regression-model-using-scikit-learn"], [28, "simple-linear-regression-model-using-scikit-learn"]], "Simple one-dimensional second-order polynomial": [[18, "simple-one-dimensional-second-order-polynomial"]], "Simple program": [[30, "simple-program"], [31, "simple-program"]], "Slightly different approach": [[31, "slightly-different-approach"]], "Sneaking in automatic differentiation using Autograd": [[31, "sneaking-in-automatic-differentiation-using-autograd"]], "Software and needed installations": [[23, "software-and-needed-installations"], [28, "software-and-needed-installations"]], "Solving Differential Equations with Deep Learning": [[2, null]], "Solving the one dimensional Poisson equation": [[2, "solving-the-one-dimensional-poisson-equation"]], "Solving the wave equation with Neural Networks": [[2, "solving-the-wave-equation-with-neural-networks"]], "Some famous Matrices": [[22, "some-famous-matrices"]], "Some simple problems": [[13, "some-simple-problems"], [30, "some-simple-problems"]], "Some useful matrix and vector expressions": [[29, "some-useful-matrix-and-vector-expressions"]], "Splitting our Data in Training and Test data": [[0, "splitting-our-data-in-training-and-test-data"], [29, "splitting-our-data-in-training-and-test-data"]], "Standard steepest descent": [[13, "standard-steepest-descent"]], "Statistical analysis and optimization of data": [[21, "statistical-analysis-and-optimization-of-data"], [28, "statistical-analysis-and-optimization-of-data"]], "Steepest descent": [[13, "steepest-descent"], [30, "steepest-descent"]], "Stochastic Gradient Descent": [[31, "stochastic-gradient-descent"]], "Stochastic Gradient Descent (SGD)": [[13, "stochastic-gradient-descent-sgd"], [31, "stochastic-gradient-descent-sgd"]], "Stochastic variables and the main concepts, the discrete case": [[25, "stochastic-variables-and-the-main-concepts-the-discrete-case"]], "Strongly Convex Case": [[31, "strongly-convex-case"]], "Support Vector Machines, overarching aims": [[8, null]], "Systematic reduction": [[3, "systematic-reduction"]], "Teachers": [[28, "teachers"]], "Teachers and Grading": [[26, null]], "Teaching Assistants Fall semester 2023": [[26, "teaching-assistants-fall-semester-2023"]], "Tentative deadllines for projects": [[26, "tentative-deadllines-for-projects"]], "Testing the Means Squared Error as function of Complexity": [[0, "testing-the-means-squared-error-as-function-of-complexity"], [29, "testing-the-means-squared-error-as-function-of-complexity"]], "Textbooks": [[27, null]], "The Algorithm before theorem": [[11, "the-algorithm-before-theorem"]], "The Breast Cancer Data, now with Keras": [[1, "the-breast-cancer-data-now-with-keras"]], "The CART algorithm for Classification": [[9, "the-cart-algorithm-for-classification"]], "The CART algorithm for Regression": [[9, "the-cart-algorithm-for-regression"]], "The CIFAR01 data set": [[3, "the-cifar01-data-set"]], "The Hessian matrix": [[30, "the-hessian-matrix"], [31, "the-hessian-matrix"]], "The Hessian matrix for Ridge Regression": [[30, "the-hessian-matrix-for-ridge-regression"], [31, "the-hessian-matrix-for-ridge-regression"]], "The Jacobian": [[29, "the-jacobian"]], "The MNIST dataset again": [[3, "the-mnist-dataset-again"]], "The OLS case": [[30, "the-ols-case"]], "The RELU function family": [[1, "the-relu-function-family"]], "The Ridge case": [[30, "the-ridge-case"]], "The SVD, a Fantastic Algorithm": [[29, "the-svd-a-fantastic-algorithm"], [30, "the-svd-a-fantastic-algorithm"]], "The Softmax function": [[1, "the-softmax-function"]], "The \\chi^2 function": [[0, "the-chi-2-function"], [28, "the-chi-2-function"], [28, "id4"], [28, "id5"], [28, "id6"], [28, "id7"], [28, "id8"]], "The bias-variance tradeoff": [[6, "the-bias-variance-tradeoff"]], "The code for solving the ODE": [[2, "the-code-for-solving-the-ode"]], "The complete code with a simple data set": [[29, "the-complete-code-with-a-simple-data-set"]], "The cost/loss function": [[29, "the-cost-loss-function"]], "The course has two central parts": [[21, "the-course-has-two-central-parts"]], "The derivative of the cost/loss function": [[30, "the-derivative-of-the-cost-loss-function"], [31, "the-derivative-of-the-cost-loss-function"]], "The equations": [[30, "the-equations"]], "The equations for ordinary least squares": [[29, "the-equations-for-ordinary-least-squares"]], "The first Case": [[30, "the-first-case"]], "The gradient step": [[31, "the-gradient-step"]], "The ideal": [[30, "the-ideal"]], "The logistic function": [[7, "the-logistic-function"]], "The mean squared error and its derivative": [[29, "the-mean-squared-error-and-its-derivative"]], "The moons example": [[8, "the-moons-example"]], "The multilayer perceptron (MLP)": [[12, "the-multilayer-perceptron-mlp"]], "The network with one input layer, specified number of hidden layers, and one output layer": [[2, "the-network-with-one-input-layer-specified-number-of-hidden-layers-and-one-output-layer"]], "The plethora of machine learning algorithms/methods": [[28, "the-plethora-of-machine-learning-algorithms-methods"]], "The sensitiveness of the gradient descent": [[30, "the-sensitiveness-of-the-gradient-descent"]], "The singular value decomposition": [[5, "the-singular-value-decomposition"], [29, "the-singular-value-decomposition"], [30, "the-singular-value-decomposition"]], "The two-dimensional case": [[8, "the-two-dimensional-case"]], "Theoretical Convergence Speed and convex optimization": [[31, "theoretical-convergence-speed-and-convex-optimization"]], "Time decay rate": [[31, "time-decay-rate"]], "To our real data: nuclear binding energies. Brief reminder on masses and binding energies": [[28, "to-our-real-data-nuclear-binding-energies-brief-reminder-on-masses-and-binding-energies"]], "Topics covered in this course: Statistical analysis and optimization of data": [[28, "topics-covered-in-this-course-statistical-analysis-and-optimization-of-data"]], "Towards the PCA theorem": [[11, "towards-the-pca-theorem"]], "Train and test datasets": [[1, "train-and-test-datasets"]], "Two-dimensional Objects": [[3, "two-dimensional-objects"]], "Type of problem": [[2, "type-of-problem"]], "Types of Machine Learning": [[28, "types-of-machine-learning"]], "Use the books!": [[19, "use-the-books"]], "Useful Python libraries": [[21, "useful-python-libraries"], [28, "useful-python-libraries"]], "Using Autograd": [[13, "using-autograd"]], "Using forward Euler to solve the ODE": [[2, "using-forward-euler-to-solve-the-ode"]], "Using gradient descent methods, limitations": [[13, "using-gradient-descent-methods-limitations"], [30, "using-gradient-descent-methods-limitations"], [31, "using-gradient-descent-methods-limitations"]], "Visualization": [[1, "visualization"], [1, "id1"]], "Visualizing the Tree, Classification": [[9, "visualizing-the-tree-classification"]], "Week 34: Introduction to the course, Logistics and Practicalities": [[28, null]], "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression": [[29, null]], "Week 36: Linear Regression and Gradient descent": [[30, null]], "Week 37: Gradient descent methods": [[31, null]], "Weekly Exercises 6": [[20, null]], "What Is Generative Modeling?": [[28, "what-is-generative-modeling"]], "What does it mean?": [[29, "what-does-it-mean"], [30, "what-does-it-mean"]], "What is Machine Learning?": [[0, "what-is-machine-learning"]], "What is a good model?": [[0, "what-is-a-good-model"], [28, "what-is-a-good-model"]], "What is a good model? Can we define it?": [[28, "what-is-a-good-model-can-we-define-it"]], "When do we stop?": [[31, "when-do-we-stop"]], "Which activation function should I use?": [[1, "which-activation-function-should-i-use"]], "Why Combine Momentum and RMSProp?": [[31, "why-combine-momentum-and-rmsprop"]], "Why Linear Regression (aka Ordinary Least Squares and family)": [[28, "why-linear-regression-aka-ordinary-least-squares-and-family"]], "Wisconsin Cancer Data": [[7, "wisconsin-cancer-data"]], "With Lasso Regression": [[30, "with-lasso-regression"]], "Writing Our First Generative Adversarial Network": [[4, "writing-our-first-generative-adversarial-network"]], "Writing our own PCA code": [[11, "writing-our-own-pca-code"]], "Writing the Cost Function": [[30, "writing-the-cost-function"]], "XGBoost: Extreme Gradient Boosting": [[10, "xgboost-extreme-gradient-boosting"]], "Yet another Example": [[30, "yet-another-example"]], "a) Expression for Ridge regression": [[17, "a-expression-for-ridge-regression"]], "scikit-learn implementation": [[1, "scikit-learn-implementation"]]}, "docnames": ["chapter1", "chapter10", "chapter11", "chapter12", "chapter13", "chapter2", "chapter3", "chapter4", "chapter5", "chapter6", "chapter7", "chapter8", "chapter9", "chapteroptimization", "clustering", "exercisesweek34", "exercisesweek35", "exercisesweek36", "exercisesweek37", "exercisesweek38", "exercisesweek39", "intro", "linalg", "project1", "schedule", "statistics", "teachers", "textbooks", "week34", "week35", "week36", "week37"], "envversion": {"sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1}, "filenames": ["chapter1.ipynb", "chapter10.ipynb", "chapter11.ipynb", "chapter12.ipynb", "chapter13.ipynb", "chapter2.ipynb", "chapter3.ipynb", "chapter4.ipynb", "chapter5.ipynb", "chapter6.ipynb", "chapter7.ipynb", "chapter8.ipynb", "chapter9.ipynb", "chapteroptimization.ipynb", "clustering.ipynb", "exercisesweek34.ipynb", "exercisesweek35.ipynb", "exercisesweek36.ipynb", "exercisesweek37.ipynb", "exercisesweek38.ipynb", "exercisesweek39.ipynb", "intro.md", "linalg.ipynb", "project1.ipynb", "schedule.md", "statistics.ipynb", "teachers.md", "textbooks.md", "week34.ipynb", "week35.ipynb", "week36.ipynb", "week37.ipynb"], "indexentries": {}, "objects": {}, "objnames": {}, "objtypes": {}, "terms": {"": [0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 26, 28, 29, 30, 31], "00": [0, 1, 5, 11, 28, 29], "000": [1, 3], "000000": [], "00000000e": [], "001": [2, 8, 13, 30, 31], "004": 5, "004113634617443131": 29, "004113634617443139": 29, "00411363461744314": 29, "004113634617443147": 29, "005b82": [], "00622f": [], "00727646693": [0, 28], "0072b2": [], "00749c": [], "008561": [], "0086649156": [0, 28], "00e0e0": [], "01": [0, 1, 2, 5, 9, 11, 13, 17, 27, 28, 29, 31], "010726": [], "0110": 25, "01719003e": [], "02": [0, 4, 7, 12, 28], "02334824": [], "023b95": [], "024c1a": [], "02857": 4, "02f": 6, "03077640549": 4, "03097597e": [], "031": 5, "04": 11, "0458": 9, "05": [4, 6], "0550ae": [], "062292565": 4, "062435": [], "06730814": [], "07": [], "0713": [0, 28], "07285": 3, "08": 25, "08078025e": [], "080808": [], "08336233266": 4, "08376632": 29, "083766322923899": 29, "0837663229239043": 29, "0917": 9, "0969da4a": [], "0d1117": [], "0n": [0, 28], "0x113e21950": 17, "1": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 24, 25, 26, 27, 28, 30, 31], "10": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 22, 24, 25, 26, 28, 29, 30, 31], "100": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 22, 25, 26, 28, 29, 30, 31], "1000": [0, 1, 2, 4, 5, 8, 11, 13, 14, 18, 19, 21, 25, 28, 30, 31], "10000": [2, 5, 6, 10, 11, 13, 25], "100000": 8, "10001": 10, "1001": 25, "1002": 25, "1003": 25, "1005": 25, "1009": 25, "101": 16, "1011": 25, "1013": 25, "1013904243": 25, "1015": 25, "102": 16, "1023": 25, "1024": 3, "1026": 25, "1027": 25, "103": 1, "1030": 25, "1037": 25, "1038": 25, "1040": 25, "1047": 25, "107": 16, "108": [], "10th": 9, "10x": [0, 28], "11": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 22, 23, 25, 27, 28, 29, 30, 31], "110": [], "1100": 25, "1101": 25, "111": [1, 7, 12], "112": 16, "11340253": [], "11590451": [], "116": 16, "116329": [], "116633": [], "117": 16, "118": 16, "12": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 18, 22, 25, 27, 28, 29, 30, 31], "120": 3, "121": [8, 9, 10, 16], "1215pm": [26, 28], "122": [8, 9, 10], "124": [0, 28], "125": 16, "127": [4, 16], "128": [3, 4, 13, 31], "129": 16, "1298": 9, "12pm": [26, 28], "13": [0, 2, 9, 12, 22, 25, 28], "131": 16, "133": 7, "135": 16, "136": 16, "14": [0, 2, 4, 6, 8, 9, 10, 12, 22, 25, 27, 29], "141": 16, "1412": 31, "141414": [], "143": 16, "1446729567": 4, "149": 16, "14g": 6, "15": [0, 2, 4, 6, 7, 8, 9, 12, 13, 23, 25, 28, 30, 31], "150": [4, 8], "152": 16, "153760": [], "156": 16, "157": [], "158": [], "159": 16, "15g": 6, "15pm": 28, "16": [1, 2, 3, 4, 5, 8, 9, 10, 25, 28, 30], "160": 16, "1603": 3, "161": 16, "162": 16, "16231451": 4, "163": 16, "16384": 3, "164": 16, "167": 16, "17": [1, 2, 8, 25], "172": 16, "173": 16, "176": 16, "178": 16, "179": 16, "1797": 1, "18": [2, 6, 7, 8, 9, 10, 25, 28], "1807": 4, "181036": [], "18392847": [], "18c1c4": [], "19": [2, 25, 28], "1940": [], "1943": 12, "19569961": 29, "19680801": [], "1970": [22, 28], "1973": 9, "1979": 6, "1_1": 12, "1_2": 12, "1_3": 12, "1cm": [0, 8, 10, 25, 28], "1d": [1, 2, 3], "1e": [2, 4, 13, 14, 31], "1e10": 14, "1e1e1": [], "1e4": 6, "1f": 1, "1k": 22, "1n": [0, 28], "1x": [0, 28], "2": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 25, 27, 31], "20": [0, 1, 2, 6, 7, 8, 16, 17, 25, 26, 28, 29, 30, 31], "200": [0, 2, 3, 4, 8, 9, 10], "2000": [0, 29], "2001": [], "2004": [13, 30], "2006": 27, "2007": [], "20072279": [], "2008": [28, 31], "2009": [], "2010": 1, "2011": [1, 31], "2012": 31, "2013": [], "2014": [4, 31], "2015": 1, "2016": [0, 28], "2018": [0, 6, 29], "2020": [], "2021": [6, 14, 29, 31], "2022": 28, "2024": [], "2025": [18, 28, 29, 30, 31], "21": [0, 1, 5, 7, 9, 12, 22, 28, 29, 30], "2116753732": 4, "215pm": [26, 28], "2167072": [], "22": [0, 1, 5, 12, 13, 22, 28, 29, 30], "221": 8, "225": 4, "22948497": [], "23": [1, 12, 22], "24": [0, 1, 22, 28], "242424": [], "24292f": [], "25": [2, 3, 4, 5, 6, 8, 9, 11, 29], "250": [2, 4, 7, 9], "25000": [], "250154": [], "252124": [], "253775": [], "255": 3, "256": [4, 31], "25x": 23, "26": [], "26303845": [], "264": [], "265": [], "265109911": 4, "266": [], "269": [], "27": 1, "270": [], "278": [30, 31], "27n_": 25, "28": [1, 3, 4], "283": [30, 31], "2830637392": 4, "2861": 25, "2873": 9, "2882": 25, "2886": 25, "2890": [0, 28], "2892": 25, "29": 29, "2915": 25, "2931": 28, "29364655": [], "294399745619595": [], "296247": [], "2968": 28, "2980": 28, "298273": [], "298375": [], "2990": 28, "2_": 12, "2_1": 12, "2_2": 12, "2_3": 12, "2_i": 12, "2_m": [6, 25], "2_t": 13, "2_x": 25, "2a": 17, "2a1968": [], "2b": 25, "2b2b2b": [], "2c8f433990d1": 31, "2cm": 8, "2d": [1, 3, 11, 12, 21, 28], "2e": 6, "2f": [0, 7, 9, 10, 11, 12, 28], "2g": 2, "2g_i": 2, "2k": 3, "2m": 6, "2mvizaqfst8": 29, "2n": [0, 2, 3, 28, 29], "2nd": 9, "2p": 25, "2pt": 4, "2x": [0, 3, 8, 13, 28], "2x_ix_jy_iy_j": 8, "2x_j": 8, "2y_i": 10, "2y_j": 8, "3": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 24, 25, 26, 28, 30, 31], "30": [0, 1, 4, 6, 7, 10, 13, 26, 31], "30000": [0, 28], "3072": 3, "31": [12, 22, 25], "315": [6, 29, 31], "3155": [0, 5, 6, 29, 30, 31], "32": [3, 4, 6, 12, 13, 22, 25, 31], "3200": 1, "3250": 1, "3297": [], "33": [12, 22, 26], "3303": [], "3310": [], "332331": [], "333": 7, "3331": [], "3337": [], "34": 22, "3436": [0, 28], "3437": [0, 28], "35": [0, 6, 23, 28, 30, 31], "3581341341": 4, "359": [5, 30], "36": [0, 5, 6, 18, 23, 25], "37": [23, 30], "370782966": 4, "38": [23, 25], "39": [0, 26, 28], "3d": [2, 3, 4, 6, 13, 16], "3d73a9": [], "3f": [1, 3, 9], "3n": 22, "3x": [2, 8], "3x_i": 2, "3y": 8, "4": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 23, 25, 28, 30, 31], "40": [1, 6, 26, 28], "400": 4, "4000": 28, "40008b9a5380fcacce3976bf7c08af5b": 31, "4050": [27, 28], "41": 22, "4155": [2, 15], "41589548": [], "42": [1, 4, 8, 9, 10, 22], "43": [0, 7, 22], "4310": 28, "436462435": 4, "437a6b": [], "44": [0, 22, 30, 31], "45": [26, 28], "46": [26, 28], "462": 7, "47": [26, 28], "473d18": [], "479465113": 4, "47958494": [], "48": [], "48257387": [26, 28], "49": [5, 6, 11], "49152": 3, "4940954": [0, 28], "4990": 25, "4992": 25, "4997": 25, "4c4b4be8": [], "4c4c7f": [9, 10], "4d": 3, "4f": 6, "4pm": [26, 28], "4y": 8, "4y_i": 10, "5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 22, 23, 25, 28, 29, 30, 31], "50": [1, 2, 3, 4, 6, 7, 8, 10, 13, 28, 29, 31], "500": [1, 3, 4, 6, 9, 10, 13, 31], "5018": 25, "506": [], "507d50": [9, 10], "50j": 13, "50x10": 1, "51": 10, "510": 1, "512132": [], "515151": [], "5177783846": 4, "53": 9, "5391cf": [], "54": [6, 25], "5411205": [], "54894451": [], "55": 1, "56": 1, "56536": [0, 28], "569": 1, "57": [0, 8, 26, 28], "571": [5, 30], "58": [10, 26, 28], "58a6ff70": [], "591317992": 4, "5ca7e4": [], "5cm": 25, "5f": [8, 31], "5x": [8, 18], "5y": 8, "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 18, 22, 25, 26, 28, 29, 30, 31], "60": [1, 3], "60000": 4, "6019067271": 4, "606439": [], "622cbc": [], "625": 7, "63": 1, "64": [1, 3, 4, 13, 22, 28, 31], "64x50": 1, "65": [1, 8, 9], "66666691": [], "66707b": [], "66ccee": [], "66e9ec": [], "6730c5": [], "6887363571": 4, "69": [16, 25], "69069n_": 25, "691": [], "6980": 31, "6e7681": [], "6e7781": [], "6f98b3": [], "6n_": 25, "7": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 22, 23, 25, 27, 28, 29, 31], "70": [1, 7], "702c00": [], "70653767": 4, "71": 1, "724": 3, "72f088": [], "73": [], "7304881": [], "737373": [], "75": [5, 6, 8, 11], "76": [26, 28], "765": 7, "77": [26, 28], "7718": 9, "7782028952": 4, "77893972": [], "78": [], "797979": [], "7998f2": [], "79c0ff": [], "7d7d58": [9, 10], "7ee787": [], "7f4707": [], "8": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 22, 25, 26, 28, 30], "80": [0, 1, 5, 8, 17, 29], "800": [4, 7], "8045e5": [], "81": 1, "815am": [26, 28], "81b19b": [], "8250df": [], "85": 1, "8702784034": 4, "8786ac": [], "88": 28, "8a4600": [], "8b949e": [], "8c8c8c": [], "8f": 6, "8g": 6, "8n": 22, "8x8": 1, "9": [0, 1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 22, 25, 28, 31], "90": 1, "9040": 9, "91": [26, 28], "912583": [], "91cbff": [], "92": [26, 28], "93": 16, "931": [0, 28], "933": [5, 30], "937": 25, "938": 25, "939": [0, 25, 28], "94": 25, "95": [1, 11], "953800": [], "954": 25, "955820c21e8b": 4, "96": 6, "960": 25, "961": 25, "962": 25, "9649652536": 4, "96611194e": [], "974eb7": [], "9780387310732": 27, "9780387848570": 27, "9781098134174": 28, "9781492032632": 27, "9781801819312": 28, "97898392": 29, "98": [0, 1, 16], "985": 25, "986": 25, "98661b": [], "989": 25, "9898ff": [9, 10], "99": [13, 16, 31], "991": 25, "992": 25, "993": 25, "996": 5, "996b00": [], "999": [9, 25, 31], "9e86c8": [], "9e8741": [], "9f4e55": [], "9x": 6, "9y": 6, "A": [2, 3, 5, 6, 7, 10, 11, 12, 13, 15, 16, 19, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31], "AND": 2, "AS": [], "AT": [], "And": [0, 3, 4, 5, 6, 9, 13, 20, 21, 23, 25, 30], "As": [0, 1, 2, 3, 4, 5, 6, 8, 10, 12, 13, 15, 16, 22, 23, 25, 28, 29, 30, 31], "At": [0, 4, 6, 13, 20, 28, 31], "BE": [0, 28], "BUT": [], "BY": [], "Be": [2, 18, 21, 28], "Being": 13, "But": [0, 1, 2, 3, 5, 6, 9, 10, 16, 25, 29], "By": [0, 3, 5, 6, 12, 13, 17, 19, 22, 28, 29, 30, 31], "FOR": [], "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30, 31], "IF": [6, 29, 31], "IN": 27, "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 18, 21, 22, 23, 25, 28, 29, 30, 31], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30, 31], "Ising": [5, 12, 29, 30], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 20, 21, 22, 23, 25, 28, 29, 30, 31], "Its": [1, 2, 4, 11], "NO": [], "NOT": [], "No": [6, 9, 28, 29, 31], "Not": [0, 1, 5, 6, 29, 30, 31], "OF": [], "ON": [], "OR": 25, "Of": 25, "On": [0, 3, 23, 25, 26, 27, 28, 31], "One": [0, 1, 3, 4, 5, 6, 7, 8, 11, 12, 13, 17, 25, 29, 30, 31], "Or": [0, 1, 6, 28], "SUCH": [], "Such": [0, 6, 12, 16, 25, 31], "THE": [], "TO": [], "That": [0, 5, 7, 10, 11, 12, 14, 23, 25, 28], "The": [4, 10, 13, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26, 27], "Then": [0, 1, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 22, 28, 30, 31], "There": [0, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 22, 23, 25, 26, 28, 29, 30, 31], "These": [0, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 17, 18, 22, 23, 25, 26, 28, 29, 30, 31], "To": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 22, 25, 29, 30, 31], "WITH": [], "With": [0, 5, 6, 8, 9, 10, 11, 12, 14, 16, 19, 22, 23, 25, 28, 29], "_": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 22, 23, 28, 29, 30, 31], "_0": [5, 8, 10, 11, 13, 29, 30], "_1": [2, 5, 6, 8, 10, 11, 12, 13, 14, 22, 29, 30, 31], "_2": [2, 5, 8, 11, 12, 13, 22, 29, 31], "_3": 22, "_4": 22, "_9": [13, 31], "__class__": 10, "__doc__": 6, "__future__": [8, 9], "__import__": [], "__init__": 1, "__main__": 2, "__name__": [2, 10], "__path__": [], "_auto1": [2, 3, 4, 5, 6, 7, 12, 13, 22, 25, 29, 30], "_auto10": [6, 12], "_auto11": 6, "_auto12": 6, "_auto2": [2, 3, 4, 5, 6, 12, 13, 22, 25], "_auto3": [3, 4, 5, 6, 12, 13, 22], "_auto4": [4, 6, 12, 13, 22], "_auto5": [4, 6, 12, 13, 22], "_auto6": [4, 6, 12, 22], "_auto7": [4, 6, 12, 22], "_auto8": [6, 12], "_auto9": [6, 12], "_build": [0, 21, 23, 27, 28], "_c": 1, "_center": [], "_compile_transl": [], "_compon": 11, "_depth": 9, "_export": [15, 16, 19], "_fraction": 9, "_i": [0, 1, 2, 5, 6, 7, 8, 11, 12, 13, 19, 23, 28, 29, 30, 31], "_j": [0, 1, 2, 3, 5, 6, 8, 13, 19, 23, 29, 30, 31], "_k": [13, 30, 31], "_l": 12, "_lambda": 6, "_leaf": 9, "_m": 10, "_multilayer_perceptron": [], "_n": [2, 5, 8, 11, 13, 29, 30, 31], "_node": 9, "_norm": [], "_p": [5, 8, 29, 30], "_parse_numpydoc_see_also_sect": [], "_pydevd_bundl": [], "_ratio": 11, "_sampl": 9, "_split": [6, 9, 23], "_t": [13, 31], "_test": [6, 23], "_varianc": 11, "_weight": 9, "a0": 3, "a0111f": [], "a0faa0": [9, 10], "a1": [0, 28], "a11": [], "a12236": [], "a2": [0, 28], "a25e53": [], "a2bffc": [], "a3": [0, 28], "a4": [0, 28], "a5d6ff": [], "a_": [0, 1, 16, 22, 28, 29], "a_0": [0, 28], "a_1a": [0, 28], "a_2a": [0, 28], "a_3": [0, 28], "a_3a": [0, 28], "a_4": [0, 28], "a_4a": [0, 28], "a_h": 1, "a_i": [0, 1, 2, 12, 28], "a_j": [1, 12], "a_k": [0, 1, 12], "aa": [], "aaa": [], "aaron": 27, "ab": [0, 2, 5, 13, 14, 28, 29, 31], "ab6369": [], "ab_channel": 21, "abandon": 1, "abe338": [], "abid": 25, "abil": [0, 10], "abl": [0, 1, 4, 5, 6, 7, 10, 12, 13, 16, 18, 19, 20, 23, 29, 30, 31], "about": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 19, 20, 21, 22, 23, 26, 31], "abov": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 25, 27, 28, 29, 31], "abovement": [6, 23, 28], "abscissa": [13, 30], "absent": 31, "absolut": [0, 2, 5, 6, 13, 28, 29, 30], "absorb": [29, 30], "abstract": [1, 31], "abund": 31, "acceler": [13, 31], "accept": [0, 3, 6, 9, 23, 29, 31], "access": [3, 11, 25, 28, 31], "accid": [4, 6], "accompani": [0, 28, 29], "accomplish": [8, 9, 13, 31], "accord": [0, 1, 2, 5, 6, 9, 12, 13, 14, 25, 28, 30, 31], "accordingli": 11, "account": [0, 3, 5, 13, 15, 16, 20, 25, 28, 31], "accumul": [12, 13, 25, 31], "accur": [0, 3, 4, 6, 10, 13, 31], "accuraci": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 28, 29, 30], "accuracy_scor": [0, 1, 10, 28], "accuracy_score_numpi": 1, "achiev": [0, 1, 5, 6, 8, 12, 22, 28, 31], "aco": 25, "acquaint": 21, "acquir": [1, 21, 28], "acr": [], "across": [1, 3, 6, 9, 17, 21, 28], "act": [1, 3, 22, 31], "action": 25, "activ": [0, 2, 3, 4, 9, 15, 24, 26, 28, 31], "activest": [], "actual": [0, 1, 4, 5, 6, 8, 11, 15, 16, 18, 22, 25, 28, 29, 30, 31], "ad": [1, 3, 4, 5, 8, 13, 15, 16, 22, 30, 31], "ada_clf": 10, "adaboostclassifi": 10, "adadelta": [13, 31], "adagrad": 23, "adam": [1, 3, 4, 23, 28], "adapt": [4, 6, 13, 17, 27, 30], "add": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 15, 16, 17, 18, 20, 25, 26, 28, 29, 30, 31], "add6ff": [], "add_": [], "add_subplot": [1, 7, 12, 14], "addendum": 5, "addeventlisten": [], "addit": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 15, 21, 22, 23, 25, 26, 27, 28, 29], "addition": [12, 13, 30, 31], "address": [1, 9, 11, 13, 28, 31], "adjac": [3, 12], "adjoint": [5, 29], "adjust": [0, 5, 12, 13, 30, 31], "admir": [0, 28], "advanc": [4, 6, 12, 27, 28, 31], "advantag": [1, 3, 5, 6, 10, 13, 19, 22, 30, 31], "adversari": 28, "advis": [], "afecionado": 28, "affect": [3, 15, 19], "affin": [0, 3, 8, 11, 29], "afford": 3, "aficionado": 28, "aforement": 14, "african": [], "after": [0, 1, 2, 4, 5, 6, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "afterward": [0, 28], "ag": [0, 7, 28, 29], "ag_0": 2, "again": [0, 1, 4, 5, 6, 7, 8, 10, 11, 12, 13, 23, 25, 28, 29, 30], "against": [1, 4, 7, 10], "agegroup": 7, "agegroupmean": 7, "aggreg": [9, 10, 31], "agorithm": 10, "agre": [5, 6, 25, 29, 30, 31], "agreement": [13, 31], "ahead": 9, "ai": [0, 27], "aid": [11, 20, 31], "aim": [0, 1, 4, 6, 7, 11, 14, 16, 17, 19, 20, 21, 22, 23, 29], "ainv": 5, "airplan": 3, "aka": 5, "al": [0, 2, 4, 16, 17, 20, 27, 28, 29, 30], "alarm": [5, 7], "aldo": 29, "algebra": [0, 3, 5, 13, 21, 29, 30], "algorithm": [0, 1, 2, 4, 5, 6, 7, 8, 13, 14, 16, 21, 22, 23, 25, 27], "align": [0, 2, 5, 6, 7, 8, 13, 25, 28, 29, 30], "all": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], "allevi": [1, 13, 30], "alloc": [3, 22], "allow": [0, 1, 2, 3, 5, 6, 8, 10, 13, 15, 21, 22, 23, 28, 29, 30, 31], "almost": [0, 1, 6, 8, 11, 13, 25, 30, 31], "alon": [2, 9, 31], "along": [2, 3, 4, 5, 6, 9, 10, 11, 15, 20, 21, 22, 28, 29, 30], "alpha": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 14, 25, 28, 29, 30, 31], "alpha_": [10, 31], "alpha_0": 3, "alpha_1": 3, "alpha_2": 3, "alpha_i": [3, 13], "alpha_k": 13, "alpha_m": 10, "alpha_n": 3, "alpha_opt": 13, "alreadi": [2, 3, 4, 5, 6, 10, 12, 15, 21, 22, 25, 28, 29, 30], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "alter": 1, "altern": [0, 1, 4, 5, 6, 8, 9, 11, 13, 15, 18, 22, 23, 28, 29, 31], "although": [0, 1, 5, 6, 8, 10, 13, 16, 19, 20, 28, 31], "alwai": [0, 3, 5, 6, 12, 13, 16, 19, 23, 25, 28, 29, 30, 31], "am": 4, "ame2016": [0, 28], "american": [], "amjith": [], "among": [0, 3, 5, 9, 10, 12, 22, 28, 29], "amongst": 5, "amount": [0, 1, 3, 4, 6, 8, 10, 14, 21], "an": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 25, 26, 27, 29, 30, 31], "an_": 25, "anaconda": [0, 1, 21, 23, 28], "analogi": 13, "analys": 6, "analysi": [1, 3, 4, 7, 14, 19, 22, 27, 31], "analyt": [2, 3, 5, 6, 7, 12, 13, 17, 21, 23, 28, 29, 30, 31], "analyz": [0, 1, 3, 4, 5, 6, 16, 23, 25, 29, 30, 31], "andrew": 1, "angl": [0, 3, 9, 29, 31], "anharmon": 3, "ani": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 19, 25, 28, 29, 31], "anim": [4, 12], "ann": 12, "annot": [0, 1, 3, 7, 8, 28], "announc": 28, "anonym": 18, "anoth": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 22, 23, 25, 28, 29, 31], "ansatz": [0, 18, 28], "answer": [0, 1, 3, 5, 6, 19, 22, 23, 26, 28], "antialias": [2, 6], "anticip": 4, "anymor": [1, 8], "anyon": [4, 8, 15], "anyth": [1, 15, 16, 25], "anytim": [26, 28], "apach": 1, "apart": [11, 13, 30, 31], "api": [1, 21, 28], "appar": 2, "appear": [0, 1, 3, 13, 22, 25], "append": [1, 3, 4, 8, 9, 13, 19, 28, 31], "appendix": 23, "appli": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 18, 23, 25, 27, 28, 29, 31], "applic": [0, 1, 3, 4, 5, 6, 7, 9, 12, 13, 16, 22, 25, 27, 28, 29, 30, 31], "apply_gradi": 4, "approach": [1, 2, 4, 5, 6, 9, 10, 11, 12, 13, 15, 16, 18, 21, 23, 25, 27, 29, 30], "approch": 23, "appropri": [2, 6, 9, 12, 13, 17, 21, 25, 31], "approv": 28, "approx": [0, 2, 3, 6, 10, 11, 13, 18, 23, 25, 28, 30, 31], "approxim": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 13, 19, 23, 25, 28, 29, 30, 31], "apt": [0, 21, 23, 28], "aq": 25, "ar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], "aragorn": 28, "arang": [1, 3, 4, 6, 7, 9, 10, 12, 13, 28, 31], "arbitrari": [1, 4, 6, 8, 12, 13, 25, 30], "arbitrarili": [0, 1, 11, 28, 31], "arc": 6, "architectur": [3, 4, 12], "archiv": 23, "area": [0, 3, 6, 27, 28], "argmax": [1, 11], "argmin": [4, 10, 14], "argsort": 11, "argu": [1, 13], "arguement": 19, "argument": [0, 2, 3, 5, 11, 12, 13, 17, 28, 29, 31], "aris": [0, 6, 12, 13, 25, 28, 30], "arithmet": [0, 13, 22, 28], "arm": [6, 29, 31], "armadillo": 22, "armin": [], "around": [0, 1, 4, 5, 6, 11, 18, 23, 25, 28], "arrai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 16, 18, 21, 23, 25, 29, 30, 31], "arrang": [3, 28], "arraybox": 13, "arriv": [0, 6, 9, 11, 22, 25, 28], "arrow": 12, "arrowprop": 8, "art": [0, 1, 21], "articl": [0, 3, 4, 6, 10, 19, 28, 29, 30, 31], "artifici": [0, 2, 7, 12, 27, 28], "artificialneuron": 12, "arug": 13, "arxiv": [3, 4, 31], "asarrai": [0, 6, 9, 29, 31], "asid": 29, "ask": [5, 6, 11, 12, 15, 19, 23], "aspect": [0, 6, 21, 28, 29], "assembl": 3, "assembli": [0, 28], "assert": 4, "assess": [0, 6, 23, 28, 29], "asset": [], "assici": 4, "assign": [0, 7, 8, 9, 12, 13, 14, 15, 24, 26, 27, 28], "associ": [0, 6, 9, 12, 14, 25, 28], "assum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 22, 23, 25, 28, 29, 30, 31], "assumpt": [0, 3, 5, 6, 9, 11, 25, 28, 29], "ast": [0, 5, 6, 28], "astyp": [4, 9, 10], "asymmetri": [0, 28], "asymptot": [4, 6, 31], "atom": [0, 28], "attain": 31, "attempt": [0, 4, 6, 7, 8, 10, 28, 29, 31], "attend": 28, "attent": [0, 22, 28], "attract": [0, 10, 28], "attribut": [0, 9, 28], "audi": [0, 28], "audio": [3, 4], "august": [28, 29], "aurelien": [0, 27, 28], "austfjel": 6, "auth": 15, "authent": 15, "author": [0, 1, 10, 25], "authour": 28, "auto": [9, 10, 25], "auto_exampl": [23, 29], "autocor": 25, "autocorrelation_tim": 25, "autocorrelform": 25, "autocovari": 25, "autoencod": [4, 21, 28], "autoencond": 21, "autograd": [21, 28], "autom": [0, 21, 27, 28], "automac": 22, "automag": 28, "automat": [0, 1, 2, 3, 4, 11, 16, 21, 22, 28], "automobil": 3, "autonom": 4, "avail": [0, 1, 4, 6, 10, 11, 20, 21, 22, 23, 24, 26, 27, 28], "averag": [0, 1, 3, 6, 9, 10, 13, 14, 25, 26, 28, 29], "avoid": [0, 4, 5, 6, 9, 11, 13, 18, 22, 29, 31], "awai": [2, 3, 6, 29, 31], "awar": [2, 10], "award": [26, 28], "ax": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22, 23, 28], "axes3d": [2, 6, 13, 30, 31], "axes_grid1": 6, "axhlin": 8, "axi": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 22, 25, 28, 29, 30, 31], "axiom": 5, "axvlin": [4, 8], "axvspan": 4, "b": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 20, 25, 26, 28, 29, 30, 31], "b1": 8, "b19db4": [], "b1bac4": [], "b2": 8, "b3": 8, "b35900": [], "b89784": [], "b_": [0, 1, 22], "b_0": 0, "b_1": [0, 2, 12, 13, 31], "b_2": [0, 13], "b_5": [13, 31], "b_group": 9, "b_i": [0, 1, 2, 12, 28], "b_ia_": [0, 28], "b_ia_i": 0, "b_index": 9, "b_j": [1, 12], "b_k": [0, 1, 12, 13, 31], "b_m": 12, "b_score": 9, "b_valu": 9, "ba": 31, "babcock": 28, "bach": 31, "bachelor": [24, 26], "back": [0, 3, 4, 5, 6, 8, 9, 10, 15, 16, 22, 25, 28, 31], "backbon": 22, "backend": [1, 4], "background": [27, 28], "backpropag": [1, 31], "backslash": [], "backtrack": 9, "backup": 22, "backward": [1, 2, 4, 12, 22, 31], "bad": [6, 17, 29], "badli": 25, "bag": [9, 21, 28], "bag_clf": 10, "baggin": 28, "baggingboot": 10, "baggingclassifi": 10, "baggingtre": 10, "bailei": [], "balanc": [6, 31], "ballpark": 18, "band": 22, "bandwidth": 22, "banner": [], "bar": [0, 6, 11, 23, 28], "barber": 27, "bare": [4, 10], "base": [0, 1, 3, 4, 5, 7, 8, 9, 10, 14, 15, 16, 17, 21, 25, 26, 27, 28, 29, 30], "basi": [5, 7, 8, 10, 11, 12, 13, 22, 29, 30], "basic": [6, 8, 12, 13, 14, 15, 21, 23, 25, 28], "basin": 31, "batch": [3, 4, 11, 12, 13, 30], "batch_shap": 4, "batch_siz": [1, 3, 4], "batchnorm": 4, "bay": 7, "bayesian": [5, 21, 27, 28], "bbbbbb": [], "beauti": [], "becaus": [0, 1, 2, 3, 4, 5, 6, 8, 9, 12, 13, 14, 28, 29, 30, 31], "becom": [0, 1, 2, 5, 6, 7, 9, 12, 13, 19, 25, 28, 29, 30, 31], "been": [0, 1, 2, 3, 4, 5, 6, 11, 12, 13, 20, 21, 22, 23, 28, 29, 31], "befor": [0, 1, 2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 17, 18, 19, 20, 22, 23, 25, 28, 29, 31], "beforehand": [0, 25, 28], "began": [], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 22, 25, 26, 28, 29, 30, 31], "behav": [1, 6, 13, 30], "behavior": [0, 1, 13, 28, 30, 31], "behaviour": [12, 31], "behind": [0, 1, 6, 8, 13, 28, 30], "being": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12, 13, 17, 20, 25, 28, 29, 30, 31], "believ": [9, 22], "belong": [7, 8, 9, 13, 14, 30], "below": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 18, 22, 23, 25, 28, 29, 30, 31], "benchmark": 10, "benefici": [1, 13], "benefit": [0, 1, 4, 11, 13, 21, 28, 30, 31], "bengio": [1, 27, 28, 29, 31], "benign": [1, 7], "besid": [4, 5, 30], "bessel": [5, 29], "best": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 18, 26, 28, 29, 30, 31], "beta": [1, 3, 10, 11, 13, 16, 17, 19, 28, 29, 30], "beta1": [], "beta2": [], "beta_": [3, 13, 17, 29], "beta_0": [1, 3, 13, 29], "beta_1": [1, 3, 10, 13, 29, 31], "beta_1m_": 31, "beta_1x_i": 13, "beta_2": [3, 13, 31], "beta_2v_": 31, "beta_3": 3, "beta_i": [3, 31], "beta_j": [13, 29], "beta_k": 13, "beta_linreg": 13, "beta_m": 10, "beta_mg_m": 10, "beta_n": 3, "better": [0, 1, 2, 3, 4, 6, 9, 10, 11, 12, 13, 19, 20, 28, 29, 31], "between": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 23, 25, 28, 29, 30, 31], "beyond": [0, 1, 5, 6, 8, 13, 28, 29, 30, 31], "bf": [13, 14, 19, 22, 25, 30], "bf5400": [], "bg": 28, "bgd": [13, 31], "bia": [0, 1, 2, 3, 5, 8, 9, 10, 12, 13, 20, 28, 29, 30], "bias": [1, 2, 3, 5, 6, 9, 12, 19, 31], "bib": [], "bibliographi": 23, "bibtex": [], "big": [0, 1, 2, 5, 6, 14, 19, 31], "bigger": [1, 6, 29], "bigr": 12, "bike": 9, "bilbo": 28, "billion": [3, 12, 21, 31], "bin": [7, 25], "binari": [0, 3, 5, 7, 9, 10, 12, 28], "binarycrossentropi": 4, "bind": 0, "binomi": [21, 25, 28], "binsboot": 6, "bioinformat": 0, "biolog": [1, 12], "bios1100": [21, 28], "bird": [0, 3], "birth": 28, "bishop": [27, 28], "bit": [1, 4, 19, 22, 25, 28], "bitwis": 25, "bivari": 2, "bk": [13, 31], "bla": [22, 28], "black": [8, 9, 14], "block": [6, 10, 21, 22, 25, 28], "blockquot": [], "blog": 28, "blogpost": 4, "blue": [0, 3], "bm": [], "bmatrix": [0, 1, 3, 5, 7, 8, 11, 13, 22, 28, 29, 30, 31], "bmi": 1, "bodi": [0, 1, 4, 12], "bold": 1, "boldfac": [0, 5, 16, 29, 30], "boldsymbol": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 23, 28, 30, 31], "boltzmann": [12, 21, 28], "book": [17, 23, 27, 28, 29], "book1": 27, "boolean": [4, 17], "boost": [1, 9, 21, 28], "boostrap": 10, "bootstrap": [1, 13, 19, 21, 23, 28, 31], "born": 31, "borrow": 28, "boston_dataset": [], "bot": 8, "both": [0, 1, 4, 5, 6, 8, 9, 10, 13, 14, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31], "bottl": 7, "bottou": 31, "bound": [8, 12, 31], "boundari": [2, 4, 8, 11, 12], "bousquet": 31, "bower": [], "box": [4, 9], "boyd": [8, 13, 30], "bracket": [4, 25], "brain": [1, 7, 12], "branch": [9, 28], "break": [0, 4, 6, 11, 14, 28, 31], "breast": [5, 7, 11], "breviti": 13, "brew": [0, 21, 23, 28], "brg": 8, "brian": [], "brief": [23, 29], "briefli": [0, 16, 19, 28], "bring": [0, 5, 6, 10, 29, 31], "britt": [26, 28], "broad": 0, "broadli": 28, "brought": [13, 21, 28], "brownle": 4, "browser": [15, 28], "brute": [3, 5, 11, 29], "bsd": [], "budget": 31, "buffer_s": 4, "bug": [], "bugfix": [], "bui": 4, "build": [0, 4, 5, 6, 10, 16, 22, 25, 28], "built": [1, 3, 4, 6], "bunch": 11, "bundl": [], "busi": [], "byte": [22, 28], "c": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31], "c1": [8, 11], "c2": [8, 11], "c4a2f5": [], "c5e478": [], "c9d1d9": [], "c_": [8, 9, 10, 13, 25, 30, 31], "c_0": 25, "c_1": 12, "c_2": 12, "c_3": 12, "c_4": 12, "c_i": [12, 13, 31], "c_k": 25, "ca": [1, 28], "caab6d": [], "cach": 10, "cal": [0, 8, 10, 12, 13, 30, 31], "calcul": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 19, 22, 25, 28, 31], "california": 23, "call": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31], "calor": [0, 29], "caltech": [], "cambridg": [13, 27, 30], "can": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 29, 30], "cancel": [0, 13, 28, 29], "cancer": [5, 10], "cancerpd": 7, "candid": [8, 9, 10, 31], "cannot": [0, 1, 4, 5, 6, 7, 8, 9, 23, 25, 29, 30, 31], "canopi": [0, 21, 23, 28], "canva": [15, 16, 19, 20, 23, 28], "cap": 5, "capabl": [0, 1, 8, 13, 21, 28], "capac": [2, 26], "capita": [], "caption": [20, 23], "captur": [4, 11, 12, 28], "car": [3, 4], "card": [0, 7, 28], "cardin": 1, "care": [11, 15, 19, 31], "carefulli": [13, 31], "carlo": [0, 6, 21, 25, 27, 28], "carri": [2, 6, 7, 23], "cart": 10, "case": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 16, 21, 22, 23, 28], "casella": 27, "cast": 1, "cat": [3, 4], "catch": 0, "categor": [0, 1, 3, 9, 11, 28], "categori": [0, 1, 3, 7, 10, 12, 14, 28], "categorical_crossentropi": [1, 3], "caus": [0, 5, 6, 25, 28, 29, 30, 31], "causal": 0, "causat": [0, 28], "cax": 1, "cb": [6, 28], "cbar": 1, "cc": [0, 1, 5, 13, 28, 29, 30, 31], "cc398b": [], "ccbb44": [], "ccc": [5, 12, 30], "cdf": 25, "cdot": [0, 2, 6, 12, 13, 14, 22, 25, 28, 30, 31], "celebr": [13, 30], "cell": 4, "center": [0, 1, 6, 7, 8, 9, 11, 14, 18, 23, 25, 28, 29, 31], "central": [0, 3, 5, 6, 8, 16, 20, 22, 28, 29], "centroid": [14, 25], "centroid_differ": 14, "centuri": 3, "certain": [0, 3, 6, 7, 9, 25, 28, 29], "cf222e": [], "cffi": [], "cg": 13, "cha": [], "chain": [0, 1, 13, 21, 25, 28], "challeng": 15, "chanc": [1, 5, 13, 25, 31], "chang": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 19, 22, 23, 25, 28, 29, 30, 31], "changelog": [], "channel": 3, "chapter": [0, 6, 10, 11, 16, 17, 19, 22, 23, 27, 28, 29, 30, 31], "chapter3": [0, 23], "charact": [0, 3, 5, 28, 29, 30], "character": [8, 9, 10, 12, 25], "characterist": [0, 1, 3, 10, 13, 28], "charg": [0, 28], "charl": [], "charset": [], "chase": 4, "chatgpt": [15, 23], "chd": 7, "chddata": 7, "cheap": [5, 29, 30, 31], "cheaper": [1, 13, 31], "check": [1, 3, 4, 5, 11, 13, 15, 16, 19, 22, 28, 31], "checkmark": 3, "checkpoint": 4, "checkpoint_dir": 4, "checkpoint_prefix": 4, "chen": 10, "cheng": 29, "chiaramont": 2, "childcar": 16, "children": 16, "choic": [0, 1, 2, 3, 4, 6, 9, 12, 13, 14, 20, 22, 28, 29, 30, 31], "choleski": [5, 22, 29, 30], "choos": [2, 3, 6, 9, 10, 11, 13, 14, 15, 18, 19, 23, 30], "chosen": [0, 1, 2, 6, 8, 9, 10, 13, 16, 25, 28, 30, 31], "chosen_datapoint": 1, "christian": 27, "christoph": [27, 28], "chunk": 31, "cifar": 3, "cifar10": 3, "circ": [1, 12, 31], "circl": [0, 8, 12, 29, 31], "circuit": 3, "circumfer": 9, "circumv": [1, 5, 13, 29, 30, 31], "citat": [], "cite": [20, 23], "ckpt": 4, "claim": [], "clariti": 25, "class": [0, 1, 3, 4, 6, 7, 8, 9, 11, 12, 13, 25, 28], "class_nam": [3, 9], "class_val": 9, "class_valu": 9, "classic": [7, 9, 13], "classif": [0, 3, 5, 6, 7, 8, 11, 12, 21, 23, 27, 28, 29], "classifi": [0, 1, 4, 7, 9, 10, 11, 28], "classificaton": 1, "classifii": 10, "claus": [], "clean": 1, "clear": [1, 5, 10, 12, 13, 31], "clearli": [0, 3, 5, 6, 7, 8, 25, 29, 30], "clever": [1, 10], "clf": [0, 6, 8, 9, 10, 28, 29], "clf3": 0, "clf_lasso": 6, "clf_ridg": 6, "cli": 15, "click": [], "clip": [3, 25, 31], "clock": 31, "clone": [15, 26], "close": [0, 1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 18, 25, 27, 28, 30, 31], "closer": [3, 5, 13, 29, 30, 31], "closest": [8, 11, 13, 14], "closur": [21, 28], "cloud": [21, 28], "cluster": [0, 1, 4, 6, 11, 21, 28], "cluster_label": 14, "cm": [1, 2, 3, 6, 8, 13, 30, 31], "cmap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 28], "cmap_arg": 6, "cmd": [9, 15], "cn_": 25, "cnn": 12, "cnn_kera": 3, "cntk": [21, 28], "co": [0, 2, 3, 6, 9, 13, 28], "code": [0, 3, 4, 6, 7, 8, 18, 19, 21, 22, 25, 27], "codec": [], "coef": [0, 28], "coef0": 8, "coef_": [0, 5, 6, 8, 9, 13, 16, 28, 29, 30, 31], "coeff": 5, "coeffici": [0, 3, 5, 6, 7, 8, 9, 13, 18, 22, 28, 29, 31], "coerc": [0, 6, 28], "coin": [10, 25], "coin_toss": 10, "col": [0, 11, 28, 29], "colab": [21, 28], "cold": 9, "colinear": [], "collabor": [20, 23], "collaps": 8, "collect": [2, 6, 10, 11, 17, 21, 25, 27, 28], "collinear": [5, 29, 30], "color": [0, 3, 4, 6, 8, 9, 10, 25, 31], "color_channel": 3, "color_cod": 6, "colorbar": [1, 6, 20], "colsample_bytre": 10, "colsaobject": 10, "column": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12, 16, 17, 18, 19, 22, 28, 29, 30, 31], "columntransform": 9, "com": [4, 6, 15, 16, 19, 20, 21, 23, 27, 28, 30, 31], "combin": [1, 2, 5, 6, 7, 10, 15, 18, 25], "come": [0, 1, 3, 4, 5, 12, 13, 14, 15, 28, 29, 30, 31], "comfort": [], "command": [0, 1, 15], "comment": [0, 4, 5, 6, 20, 23], "commerci": [0, 21, 23, 28], "commit": 15, "commod": [0, 28], "common": [0, 1, 3, 5, 6, 7, 9, 11, 13, 14, 16, 23, 25, 28, 29, 30, 31], "commonli": [0, 1, 4, 6, 7, 9, 13, 14, 29, 31], "commonmark": [], "commun": [0, 12, 15, 23], "commut": 3, "commutatitav": 3, "compact": [0, 1, 3, 5, 6, 7, 9, 11, 12, 13, 14, 28, 29], "compair": 0, "compar": [0, 3, 4, 5, 6, 11, 13, 18, 22, 23, 28, 29, 30, 31], "comparison": [2, 4, 13], "compat": 7, "compens": 31, "compet": 0, "competit": 10, "compil": [0, 1, 3, 4, 13, 21, 22, 28], "complet": [0, 2, 3, 4, 9, 12, 15, 16, 17, 18, 19, 20, 28], "completenn": 12, "complex": [1, 5, 8, 9, 11, 12, 13, 16, 19, 28, 30, 31], "complianc": [], "complic": [0, 1, 9, 13, 23, 28, 30, 31], "compoment": 29, "compon": [0, 1, 3, 4, 5, 6, 7, 9, 14, 16, 21, 28, 29, 30], "components_": 11, "compos": [9, 12, 13, 14, 21, 28], "compphys": [0, 6, 16, 20, 21, 23, 24, 26, 27, 28, 29, 30], "compress": [0, 28, 29], "compris": 6, "compromis": [5, 29, 30], "compulsori": [21, 28], "comput": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 18, 21, 22, 23, 24, 25, 27, 28, 29, 30], "computation": [0, 3, 6, 9, 13, 25, 28, 30, 31], "computationalscienceuio": 28, "computerlab": 23, "concaten": [2, 4, 6, 14], "concav": [1, 13, 29, 30], "concentr": 10, "concept": [0, 2, 21, 28, 29], "conceptu": [12, 13, 30], "concern": [0, 1, 4, 7, 28, 30], "concic": 28, "conclud": [0, 5, 13, 31], "conclus": 1, "cond": 2, "conda": [0, 1, 21, 23, 28], "condis": 29, "condit": [0, 2, 4, 5, 6, 8, 9, 11, 13, 25, 28, 29, 31], "conduct": 21, "condwav": 2, "confid": [0, 5, 6, 7, 8, 19, 28, 29], "configur": 3, "confirm": [5, 12], "conform": [], "confus": [5, 6, 7, 10, 22, 29], "confusion_matrix": 9, "congruenti": 25, "conjug": [4, 8], "conjugaci": 13, "conjunct": 3, "connect": [0, 1, 3, 4, 9, 11, 12, 13, 22, 28, 29, 30], "consensu": 31, "consequ": [5, 6, 8, 10, 12, 13, 29, 30, 31], "consequenti": [], "conserv": [5, 14, 29, 30], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 16, 19, 22, 23, 25, 28, 29, 30, 31], "consider": [0, 1, 5, 13, 28, 29, 30], "consist": [1, 2, 3, 4, 6, 12, 13, 23, 25, 29, 30], "consol": [], "const": [], "constant": [0, 2, 4, 5, 6, 8, 12, 13, 16, 18, 25, 28, 29, 30, 31], "constitu": [0, 28], "constitut": [2, 6], "constrain": [1, 3, 5, 7, 11, 30], "constraint": [5, 6, 8, 13, 29, 30], "construct": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 22, 25, 28, 29], "constructor": [], "consum": 31, "contact": [0, 28], "contain": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 18, 19, 22, 23, 25, 27, 28, 29, 30, 31], "contemporari": 28, "content": [1, 15, 20, 21, 22, 28, 30, 31], "context": [6, 10, 13, 23, 30, 31], "contigu": 22, "contin": 19, "continu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 19, 22, 23, 25, 28, 29, 30, 31], "contour": [9, 10, 13], "contourf": [8, 9, 10], "contract": [], "contrast": [1, 4, 9, 10, 12, 28, 31], "contribut": [0, 3, 5, 13, 18, 25, 28, 29, 30, 31], "contributor": [0, 23], "control": [0, 1, 3, 9, 13, 15, 21, 28], "conv": [3, 4], "conv2d": [3, 4], "conv2dtranspos": 4, "convei": 28, "conveni": [5, 6, 12, 13, 22, 23, 28, 30, 31], "convent": [12, 29], "converg": [1, 2, 4, 5, 8, 13, 14, 18, 29, 30], "convergencewarn": [], "convers": [20, 31], "convert": [0, 1, 4, 5, 9, 11, 13, 22, 28, 29, 30], "converttomatrix": 4, "convex": [4, 5, 7, 29], "convinc": [13, 30], "convolut": [1, 4, 21, 28], "cool": [4, 9], "coolwarm": 6, "coordin": [5, 12, 14, 29, 30, 31], "coorel": [], "copi": [0, 1, 14, 15, 29], "copyright": [], "core": 10, "corel": 28, "coronari": 7, "corr": [5, 7, 11, 29], "correalt": [11, 21], "correct": [0, 1, 2, 3, 4, 5, 7, 13, 15, 19, 20, 22, 25, 28, 29, 30], "correctli": [1, 2, 6, 7, 10, 18, 19, 23], "correl": [0, 1, 3, 5, 6, 7, 10, 12, 13, 21, 25, 28, 30, 31], "correlation_matrix": [5, 7, 11, 29], "correspond": [0, 3, 5, 6, 8, 9, 11, 12, 21, 22, 23, 25, 28, 29, 30], "cortex": 12, "cosin": [3, 6], "cost": [0, 2, 3, 5, 6, 7, 8, 9, 12, 13, 16, 17, 18, 19, 23, 28], "cost_deep_grad": 2, "cost_funct": 2, "cost_function_deep": 2, "cost_function_deep_grad": 2, "cost_function_grad": 2, "cost_grad": 2, "cost_histori": [], "cost_ol": [], "cost_ridg": [], "cost_sum": 2, "costli": 31, "costol": [13, 31], "could": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 22, 23, 25, 28, 29, 30, 31], "coulomb": [0, 28], "count": [0, 9, 15, 24, 25, 26, 28], "counteract": 31, "counterpart": 28, "countor": 13, "coupl": [4, 5, 6], "cours": [0, 1, 3, 5, 11, 15, 16, 17, 19, 20, 23, 26, 29], "coursework": 15, "courvil": [27, 28, 29, 31], "cov": [5, 6, 11, 22, 25, 28, 29], "cov_xi": [5, 11, 29], "cov_xx": [5, 11, 29], "cov_yi": [5, 11, 29], "covari": [0, 7, 21, 22, 28, 30], "covariance_matrix": [5, 11, 14], "cover": [0, 5, 21, 26, 27, 29, 30], "covert": [0, 28], "covxi": 25, "covxx": 25, "covxz": 25, "covyi": 25, "covyz": 25, "covzz": 25, "cpu": 1, "craft": 3, "crash": 31, "creat": [1, 3, 4, 5, 9, 10, 11, 12, 15, 18, 19, 21, 28, 31], "create_biases_and_weight": 1, "create_convolutional_neural_network_kera": 3, "create_neural_network_kera": 1, "create_x": [5, 11], "credit": [0, 7, 26, 28], "crim": [], "crime": [], "criteria": [0, 4, 9, 10, 14, 25, 28], "criterion": [9, 10, 13, 18, 30, 31], "critic": [6, 23, 29], "critiqu": 23, "cross": [0, 1, 3, 7, 9, 10, 13, 15, 21, 25, 28, 29, 30, 31], "cross_entropi": 4, "cross_val_scor": 6, "cross_valid": [7, 10], "crossvalid": 6, "crucial": [1, 25, 31], "cs231": 3, "csr_matrix": [22, 28], "css": [], "csv": [0, 4, 6, 7, 9], "ctnk": 1, "cubic": 0, "cumbersom": 5, "cumsum": [10, 11, 28], "cumul": [7, 10, 25, 31], "cumulative_heads_ratio": 10, "cup": 5, "current": [1, 2, 3, 4, 13, 14, 15, 16, 27, 30, 31], "curs": [0, 29], "curv": [6, 7, 10, 12, 23], "curvatur": [13, 30, 31], "custom": [6, 14], "custom_cmap": [9, 10], "custom_cmap2": [9, 10], "custom_lin": [], "cutpoint": 9, "cv": [6, 7, 10], "cvxbook": [13, 30], "cvxopt": [5, 8, 29], "cycl": [1, 12], "cycler": [], "d": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20, 22, 25, 26, 28, 29, 30, 31], "d166a3": [], "d2_g_t": 2, "d2a8ff": [], "d4d0ab": [], "d71835": [], "d9dee3": [], "d_f": [13, 30], "d_g_t": 2, "d_net_out": 2, "da": 3, "dagger": [5, 22, 29, 30], "dai": [1, 9, 21], "damag": [], "damp": 3, "darget": 9, "darkr": 25, "dat": [0, 28], "dat_id": [0, 6, 7, 9, 28], "data": [2, 4, 5, 8, 10, 12, 13, 14, 16, 19, 20, 22, 23, 27, 30, 31], "data1": 14, "data2": 14, "data3": 14, "data4": 14, "data_id": [0, 6, 7, 9, 28], "data_indic": 1, "data_panda": 28, "data_path": [0, 6, 7, 9, 28], "databas": 1, "datafil": [0, 6, 7, 9, 28], "datafram": [0, 4, 5, 7, 9, 11, 28, 29], "datapoint": [1, 5, 6, 7, 11, 13, 16, 30, 31], "datasci": [15, 16, 19], "dataset": [0, 4, 6, 7, 8, 9, 10, 11, 13, 14, 16, 23, 28, 30, 31], "datatyp": 4, "date": [15, 18, 23, 28, 29, 30, 31], "daughter": 10, "davi": [], "david": 27, "dbb7ff": [], "dbh": 1, "dbo": 1, "dcc6e0": [], "dcomposit": 22, "ddot": 2, "de": 31, "dead": 1, "deadlin": [15, 20], "deal": [0, 1, 3, 5, 6, 8, 11, 13, 14, 19, 22, 25, 28, 29, 30, 31], "dealt": 0, "debt": 7, "debug": [0, 5, 6, 29, 30, 31], "debugg": [], "decad": [0, 3, 31], "decai": [0, 13, 25, 28], "decemb": [26, 28], "decent": 10, "decid": [0, 2, 3, 5, 6, 9, 18, 29, 30, 31], "decim": [0, 28], "decis": [0, 1, 8, 11, 21, 27, 28], "decision_funct": 8, "decision_tre": 9, "decisiontreeclassifi": [9, 10], "decisiontreeregressor": [0, 9, 10], "declar": [0, 4, 20, 22, 28], "declare_namespac": [], "decompos": [5, 6, 22, 29, 30], "decomposit": [0, 6, 12, 28], "decompost": [5, 29, 30], "deconvolut": 3, "decorrel": [10, 13, 31], "decreas": [1, 2, 4, 5, 6, 10, 11, 13, 19, 30, 31], "dedic": 20, "deduc": [0, 28], "deep": [3, 7, 12, 13, 21, 27, 29, 30], "deep_neural_network": 2, "deep_param": 2, "deep_tree_clf": [9, 10], "deep_tree_clf1": 9, "deep_tree_clf2": 9, "deepen": [5, 21, 28], "deeper": [0, 3, 4, 28], "deeplearningbook": [27, 28, 30, 31], "deer": 3, "def": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 25, 28, 29, 30, 31], "def_covari": 25, "default": [0, 1, 2, 4, 6, 7, 22, 28, 29], "default_tim": 4, "defect": [5, 29, 30], "defici": [5, 29, 30], "defin": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 22, 23, 25, 29, 30, 31], "definit": [1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 22, 25, 29, 30, 31], "defint": 25, "degre": [3, 5, 6, 8, 9, 10, 11, 15, 16, 19, 20, 23, 25, 28, 30, 31], "deisenroth": 29, "del": 1, "delet": [6, 15], "delimit": 4, "deliv": [15, 24, 28], "delta": [0, 2, 3, 6, 8, 12, 13, 14, 28, 31], "delta_": [1, 22], "delta_0": 3, "delta_1": 3, "delta_2": 3, "delta_3": 3, "delta_4": 3, "delta_5": 3, "delta_h": [0, 1, 28], "delta_j": [3, 12], "delta_k": 12, "delta_l": [1, 3], "delta_momentum": [13, 31], "delta_n": [0, 3, 28], "delug": 21, "delv": 0, "demand": [13, 30], "demonstr": [0, 3, 5, 6, 7, 11, 12, 19, 21, 28, 29, 30, 31], "den": 4, "denomin": [1, 5, 31], "denot": [1, 2, 6, 7, 13, 25, 30, 31], "dens": [1, 3, 4], "densiti": [0, 2, 6, 25], "depart": [26, 28, 29, 30, 31], "depend": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 21, 22, 23, 25, 28, 29, 30, 31], "depict": 25, "deploy": [0, 21, 23, 28], "depth": [0, 3, 9, 10, 22], "der": [], "deriv": [0, 1, 2, 6, 7, 8, 10, 11, 13, 18, 21, 23, 28], "derivati": 13, "derivative_fn": 13, "descend": [5, 9, 11, 29, 30], "descent": [0, 1, 3, 7, 8, 12, 28, 29], "describ": [0, 2, 4, 5, 6, 8, 10, 11, 12, 13, 19, 20, 22, 23, 28, 31], "descript": [0, 8, 9, 20, 23, 28], "design": [0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 17, 18, 23, 28, 30, 31], "designmatrix": [0, 28], "desir": [0, 2, 4, 5, 13, 14, 28, 29, 30, 31], "desktop": 15, "despit": [1, 12, 31], "destroi": 22, "det": [5, 22, 29, 30], "detail": [0, 6, 11, 13, 14, 18, 22, 23, 29, 30, 31], "detect": [3, 8, 12], "determin": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 18, 22, 25, 28, 29, 30, 31], "determinist": [7, 13, 25, 30, 31], "dev": [1, 23], "develop": [0, 3, 5, 8, 10, 11, 12, 21, 22, 23, 28, 29], "deviat": [0, 1, 2, 4, 5, 6, 17, 18, 19, 23, 25, 28, 29, 31], "devis": 12, "df": [4, 8, 11, 13, 28], "df1": 28, "di": [], "diag": [5, 8, 29, 30, 31], "diagnost": [1, 10], "diagon": [0, 5, 7, 13, 18, 19, 22, 25, 28, 29, 30, 31], "diagonaliz": [5, 29, 30], "diagram": 10, "diagsvd": 6, "dice": [6, 25], "dict": [6, 8], "dictionari": [], "did": [0, 1, 5, 6, 7, 10, 11, 14, 16, 23, 28], "die": 1, "diff": 2, "diff1": 2, "diff2": 2, "diff_ag": 2, "diffeent": 8, "differ": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30], "differenti": [0, 3, 16, 21, 22, 28, 29, 30], "difficult": [0, 1, 6, 10, 13, 25, 28, 31], "difficulti": [0, 1, 13, 28, 30, 31], "diffonedim": 2, "digit": [0, 1, 3, 4, 6, 26, 28], "dilemma": [13, 31], "dilut": 1, "dim": [4, 11, 14, 22], "dimens": [0, 1, 2, 3, 4, 5, 8, 11, 14, 16, 22, 28, 29, 30], "dimension": [0, 4, 5, 6, 9, 11, 13, 14, 19, 21, 22, 23, 28, 29, 30, 31], "dimensionless": [0, 3, 28], "diment": 22, "diminish": 31, "dimnsion": 4, "diod": 3, "direct": [0, 1, 2, 4, 11, 12, 13, 14, 28, 29, 30, 31], "directli": [1, 4, 5, 6, 18, 25, 29, 30], "directori": [], "disadvantag": [0, 28, 31], "disappear": [3, 6], "disc_loss": 4, "disc_tap": 4, "discard": [6, 11, 31], "disciplin": [0, 3, 12], "disclaim": 25, "discord": 28, "discourag": [13, 15, 30], "discov": [0, 28], "discover": 5, "discret": [1, 3, 5, 7, 13], "discrimin": [4, 7, 10, 11], "discriminator_loss": 4, "discriminator_loss_list": 4, "discriminator_model": 4, "discriminator_optim": 4, "discuss": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 20, 21, 22, 23, 25, 27, 28, 29, 30, 31], "diseas": 7, "disguis": [6, 29, 31], "disk": 31, "disord": [1, 7], "displai": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 23, 25, 28, 29, 31], "displaystyl": [0, 5, 17, 28, 29, 30, 31], "disregard": [0, 28], "dissimilar": [11, 14], "dist": 14, "distanc": [8, 9, 11, 14, 25], "distance_list": 9, "distinct": [3, 7, 8, 9, 10, 14], "distinctli": 8, "distinguish": [0, 4, 7, 8, 25, 28], "distplot": [], "distribut": [0, 1, 4, 6, 7, 10, 11, 13, 14, 18, 19, 21, 22, 23, 28, 29, 30, 31], "distrubut": [0, 21, 23, 28], "div": [], "dive": [0, 8, 22, 28], "diverg": [1, 13, 30, 31], "divid": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12, 18, 19, 25, 28, 29, 31], "divis": [6, 8, 9, 13, 18, 22, 25, 31], "dl": [], "dna": 7, "dnn": [0, 1, 2, 4, 12, 28], "dnn1": 4, "dnn2_gru2": 4, "dnn_kera": 1, "dnn_model": 1, "dnn_numpi": 1, "dnn_scikit": [0, 1, 28], "do": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 22, 23, 28, 29, 30], "doc": [0, 15, 16, 19, 21, 23, 24, 26, 27, 28], "document": [4, 13, 15], "docutil": [], "doe": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 17, 18, 19, 22, 23, 25, 28, 31], "doesn": [3, 9, 12, 28, 31], "dog": [1, 3, 4], "dollar": [], "domain": [5, 8, 13, 23, 30], "domcontentload": [], "domin": [0, 28], "don": [0, 1, 3, 5, 6, 8, 11, 13, 15, 16, 21, 23, 28, 29, 31], "done": [0, 2, 3, 4, 5, 6, 9, 10, 11, 13, 16, 20, 22, 23, 28, 29, 30, 31], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 18, 22, 23, 25, 28, 29, 30, 31], "doubl": [3, 4, 16, 22, 28], "doubli": 1, "doubt": 23, "down": [0, 3, 6, 9, 11, 12, 13, 30, 31], "download": [0, 1, 3, 5, 6, 15, 20, 22, 27, 28], "downsampl": 3, "dozen": 1, "dq": 6, "draft": 20, "drag": 13, "dragon": [], "dramat": 11, "drastic": 4, "draw": [4, 6, 10, 13, 30], "drawback": [0, 1, 3, 13, 29, 30, 31], "drawn": [1, 4, 6, 7, 11, 25, 28], "drive": [3, 4], "driven": 3, "drop": [0, 1, 5, 6, 11, 13, 25, 28, 29, 30], "dropna": [0, 6, 28], "dropout": 4, "dt": [2, 3, 13, 25], "dtype": [0, 1, 3, 4, 14, 22, 28], "dub": [0, 28], "due": [1, 2, 5, 6, 8, 10, 12, 13, 18, 26, 28, 29, 30, 31], "dummi": [], "dure": [0, 1, 3, 4, 8, 9, 11, 20, 21, 23, 28, 31], "dwell": [], "dwh": 1, "dwo": 1, "dx": [2, 3, 8, 25], "dx_1": 25, "dx_1p": 6, "dx_2p": 6, "dx_mp": 6, "dx_n": 25, "dxp": 6, "dy": [1, 8, 25], "dynam": 4, "dz": 8, "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 26, 28, 29, 30, 31], "e1e1e1": [], "e_": [0, 2, 28], "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 22, 24, 25, 26, 28, 29, 30, 31], "eapprox": [0, 28], "earli": [1, 13, 31], "earlier": [0, 5, 7, 8, 9, 11, 12, 13, 20, 28, 29], "earthexplor": 6, "eas": [6, 9, 14], "easi": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 21, 22, 28, 29, 30, 31], "easier": [5, 6, 8, 9, 13, 15, 20, 23, 25, 28, 29, 30], "easiest": [13, 18], "easili": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 28, 29, 30, 31], "eastern": [26, 28], "ebind": [0, 28], "eblock": 9, "ec8e2c": [], "econometr": 28, "economi": 5, "ecosystem": [21, 28], "ect": 24, "edg": 3, "edgecolor": 6, "edit": [], "editor": [15, 20], "edu": [13, 23, 30], "educ": [0, 23, 28], "ee6677": [], "eff": 25, "effect": [1, 4, 10, 13, 16, 17, 18, 25, 31], "effic": 1, "effici": [0, 3, 10, 13, 21, 22, 25, 28, 31], "effort": 19, "efron": 6, "egrad": 13, "eig": [5, 11, 13, 22, 25, 28, 29, 30, 31], "eigen": 25, "eigenpair": [5, 11, 29, 30], "eigenvalu": [0, 5, 8, 11, 13, 22, 28, 29, 30, 31], "eigenvector": [5, 11, 13, 29, 30], "eight": [22, 28], "eigval": [22, 25, 28], "eigvalu": [11, 13, 30, 31], "eigvec": [22, 25, 28], "eigvector": [11, 13, 30, 31], "eir": [26, 28], "eispack": [22, 28], "either": [1, 5, 6, 7, 8, 9, 10, 11, 13, 18, 19, 23, 25, 28, 29, 30, 31], "eivind": 26, "eivinsto": 26, "ekstr\u00f8m": 4, "elabor": 25, "elarn": 3, "electr": [0, 3, 12, 28], "electron": 28, "eleg": 11, "element": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 19, 20, 21, 22, 23, 27, 29, 31], "elementari": [10, 13, 22], "elementwis": [3, 13], "elementwise_grad": [2, 13], "elessar": 28, "elif": 14, "elim": 22, "elimin": [3, 8], "elin": [26, 28], "ell_": [], "ellipsi": 16, "els": [1, 3, 4, 7, 9, 12, 13, 16, 22], "elu": 1, "elus": [0, 28], "em": [], "email": [24, 26, 28], "emb": [], "embed": [0, 11, 29], "embodi": [6, 23], "emit": 25, "emner": 27, "emph": 31, "emphas": [0, 10, 21, 28], "emphasi": [0, 21, 27, 28], "empir": [1, 11, 25], "emploi": [0, 1, 5, 6, 11, 13, 25, 28, 29, 30], "employ": 0, "empti": [6, 10, 15], "emul": 12, "en": [21, 23, 27], "enabl": [11, 31], "enbodi": 6, "encod": [0, 3, 5, 9, 11, 14, 28, 29, 30], "encompass": [0, 23, 25], "encount": [0, 1, 5, 7, 13, 15, 23, 25, 28, 29, 30, 31], "encourag": [15, 23], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22, 25, 26, 28, 29, 30, 31], "endblock": [], "endfor": [], "endif": [], "endors": [], "endpoint": [3, 6], "energi": [0, 4, 6], "enforc": 12, "eng": 27, "engin": [0, 1, 3, 4, 21, 28], "english": 23, "enjoi": 31, "enocurag": 23, "enorm": 3, "enough": [0, 6, 13, 28, 30, 31], "ensembl": [1, 9, 28], "ensur": [0, 1, 2, 3, 5, 6, 11, 13, 18, 25, 29, 30, 31], "entail": 28, "enter": [5, 6, 29, 30, 31], "enthought": [0, 21, 23, 28], "entir": [1, 3, 7, 9, 21, 25, 28, 31], "entireti": [], "entiti": [9, 12, 22, 28], "entri": [0, 5, 8, 11, 12, 22, 28, 29, 31], "entropi": [1, 3, 7, 10, 13, 28, 30, 31], "enumer": [0, 1, 2, 3, 4, 6, 8, 28, 29, 31], "env": 25, "environ": [2, 21, 23, 28], "environemnt": 15, "eo": [0, 6], "eol": 0, "eosfit": 0, "epoch": [0, 1, 3, 4, 12, 13, 28, 31], "eppstein": [], "epsilon": [0, 5, 6, 7, 13, 23, 28, 29, 30, 31], "epsilon_": [0, 28], "epsilon_0": [0, 28], "epsilon_1": [0, 28], "epsilon_2": [0, 28], "epsilon_i": [0, 28, 29], "eq": [3, 13, 14, 22, 25, 30], "eqnarrai": [3, 5, 6], "equal": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 16, 18, 22, 23, 25, 28, 29, 30, 31], "equat": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 17, 19, 22, 25, 28, 31], "equilibrium": [2, 12], "equiv": [3, 13, 22, 25, 30, 31], "equival": [0, 1, 5, 7, 8, 11, 13, 21, 22, 28, 29, 30, 31], "equivel": 19, "erf": 25, "eriador": 28, "eric": [], "err": [0, 10], "err_": 6, "err_sqr": 2, "errat": [13, 30, 31], "erron": 2, "error": [1, 2, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 18, 19, 21, 22, 23, 25, 31], "error_estimate_corr_tim": 25, "error_hidden": 1, "error_output": 1, "escap": [13, 30, 31], "escapehtml": [], "especi": [1, 3, 9, 12, 13, 15, 18, 23, 31], "essenti": [0, 5, 6, 9, 10, 12, 14, 15, 23, 25, 29, 30, 31], "establish": [0, 6, 10, 11, 16, 23], "estim": [0, 1, 5, 6, 7, 10, 11, 13, 19, 21, 25, 28, 29, 30, 31], "estimated_mse_fold": 6, "estimated_mse_kfold": 6, "estimated_mse_sklearn": 6, "et": [0, 2, 4, 16, 17, 20, 27, 28, 29, 30], "eta": [0, 1, 3, 8, 12, 13, 18, 28, 30, 31], "eta0": [8, 13], "eta_": 13, "eta_j": 31, "eta_t": [13, 31], "eta_v": [0, 1, 3, 28], "etc": [0, 1, 3, 5, 7, 8, 9, 11, 12, 13, 14, 21, 22, 23, 25, 29, 30, 31], "ethic": 21, "euclidean": [0, 14, 29, 31], "euler": [], "evalu": [0, 2, 3, 4, 5, 6, 9, 13, 15, 16, 17, 19, 23, 25, 28, 29, 30, 31], "evalut": [13, 23], "even": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 21, 22, 25, 28, 29, 30, 31], "evenli": 4, "event": [5, 7, 10, 25], "eventu": [0, 5, 6, 11, 12, 13, 23, 26, 29, 30, 31], "everi": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15, 21, 25, 26, 28, 29, 30, 31], "everyth": [4, 12, 16, 18], "everywher": [4, 13, 30], "evolv": 0, "exact": [0, 5, 11, 12, 13, 22, 25, 28, 29, 31], "exactli": [0, 3, 4, 6, 12, 18, 21, 29, 31], "exam": 28, "examin": 6, "exampl": [0, 5, 11, 12, 13, 15, 16, 18, 20, 21, 22, 23, 25, 27], "exce": [1, 12, 13, 31], "exceed": 31, "excel": [0, 1, 4, 5, 10, 20, 23, 28, 29], "except": [3, 4, 6, 8, 9, 22], "excess": [0, 28], "exchang": 31, "excit": 0, "exclud": [1, 6, 12, 29, 31], "exclus": [0, 1, 3, 6, 25, 28], "execut": [2, 5, 13, 15, 29, 30, 31], "exemplari": [], "exemplifi": [13, 31], "exercic": [26, 28], "exercis": [5, 21, 23, 24, 26, 28, 30, 31], "exhaust": [6, 31], "exhibit": [0, 5, 6, 8, 28, 29], "exist": [0, 1, 2, 3, 5, 6, 7, 8, 9, 13, 19, 22, 23, 28, 30, 31], "exit": [5, 22, 29, 30], "exp": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 25, 29, 30, 31], "exp_term": 1, "expand": [5, 7, 11, 13, 30], "expans": [0, 3, 5, 8, 10, 12, 13, 28, 29, 30], "expect": [0, 1, 5, 6, 7, 11, 12, 13, 15, 18, 21, 23, 28, 29, 31], "expectation_value_of_h_wrt_p": 25, "expens": [6, 10, 13, 16, 30, 31], "experi": [0, 1, 6, 8, 13, 15, 21, 23, 28, 29, 30, 31], "experiment": [0, 4, 6, 9, 25, 28], "expert": [1, 9], "explain": [0, 6, 9, 10, 11, 13, 16, 19, 23, 28, 30], "explained_variance_ratio_": 11, "explan": [], "explanatori": [0, 28], "explicit": [0, 3, 6, 13, 22, 23, 28, 29, 30, 31], "explicitli": [0, 4], "explod": 1, "exploit": [0, 3, 12, 13, 28, 31], "explor": [1, 4, 6, 8, 13, 18, 21, 23, 28, 30, 31], "expon": 1, "exponenti": [0, 1, 5, 6, 10, 13, 25, 28, 30], "export": [9, 15, 16, 19, 20], "export_graphviz": 9, "export_text": 9, "exporttext": 9, "expos": 21, "express": [0, 2, 3, 5, 6, 7, 10, 12, 13, 18, 22, 23, 25, 28, 30, 31], "exptmean": 25, "exptvari": 25, "extend": [0, 2, 7, 11, 13, 21, 28, 31], "extend_path": [], "extens": [0, 12, 15, 21, 28], "extent": [0, 1, 6, 27], "extern": [3, 6, 9], "extra": [1, 3, 5, 15, 26, 28, 29, 30], "extract": [0, 3, 5, 6, 7, 8, 11, 13, 16, 17, 22, 28, 29], "extrapol": [0, 28], "extrem": [0, 1, 4, 5, 6, 7, 8, 9, 13, 15, 16, 22, 29, 30, 31], "extremum": [13, 30], "extrins": 11, "ey": [0, 5, 6, 13, 14, 18, 22, 28, 29, 30, 31], "f": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 19, 22, 25, 26, 28, 29, 30, 31], "f1": 13, "f11": [0, 28], "f12": [0, 28], "f13": [0, 28], "f1_grad": 13, "f1d": 13, "f2": 13, "f26196": [], "f2_grad_x1": 13, "f2_grad_x1_analyt": 13, "f2_grad_x2": 13, "f2_grad_x2_analyt": 13, "f2f2f2": [], "f3": 13, "f3_grad": 13, "f3_grad_analyt": 13, "f4": 13, "f4_grad": 13, "f4_grad_analyt": 13, "f5": 13, "f5_grad": 13, "f5a394": [], "f5ab35": [], "f5f5f5": [], "f6": 13, "f6_for": 13, "f6_for_grad": 13, "f6_grad_analyt": 13, "f6_while": 13, "f6_while_grad": 13, "f7": 13, "f78c6c": [], "f7_grad": 13, "f7_grad_analyt": 13, "f8": 13, "f8_grad": 13, "f8f8f2": [], "f9": [0, 13, 28], "f9_altern": 13, "f9_alternative_grad": 13, "f9_grad": 13, "f_": 10, "f_0": [3, 10], "f_1": [10, 13, 30], "f_2": [12, 13, 30], "f_3": 12, "f_d": 25, "f_grad": 13, "f_grad_analyt": 13, "f_i": [0, 6, 12, 16], "f_m": [3, 10], "f_n": 3, "f_vec": 2, "face": [13, 28, 30], "facecolor": [6, 8, 25], "facil": [0, 21], "facilit": 12, "fact": [0, 1, 3, 5, 9, 11, 12, 13, 28, 29, 30, 31], "facto": 31, "factor": [0, 1, 3, 5, 6, 9, 10, 11, 13, 22, 25, 28, 29, 30], "factori": 13, "fad000": [], "fade": 6, "fae4c2": [], "fafab0": [9, 10], "fail": [0, 6, 13, 26, 28, 30], "failur": 7, "fairli": [1, 2, 18, 25, 31], "faisal": [16, 29], "fake": 4, "fake_loss": 4, "fake_output": 4, "fall": [8, 9, 24], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 14, 16, 17, 22, 28, 29, 30, 31], "famili": [0, 7, 8, 25, 29, 31], "familiar": [0, 3, 5, 6, 8, 15, 21, 22, 23, 25, 28], "famou": [6, 12], "far": [0, 3, 4, 5, 6, 8, 11, 12, 13, 14, 16, 20, 28, 29, 30, 31], "fashion": [0, 9, 10, 28, 31], "fast": [1, 3, 6, 10, 12, 13, 21, 25, 28, 30, 31], "faster": [1, 11, 13, 31], "fastest": [13, 22, 30], "fatal": [], "favor": [7, 31], "favorit": 25, "fc": 3, "fcfcfc": [], "fdac54": [], "fdf2e2": [], "featur": [0, 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 15, 17, 18, 19, 21, 25, 28, 30, 31], "feature_nam": [1, 7, 9], "feautur": 9, "fed": 1, "feed": [0, 2, 3, 11, 21, 28], "feed_forward": 1, "feed_forward_out": 1, "feed_forward_train": 1, "feedback": [4, 20, 28], "feeddorward": 4, "feedforward": [1, 4, 12], "feel": [0, 5, 6, 11, 13, 15, 16, 18, 21, 23, 26, 28], "feet": [], "fefef": [], "fefeff": [], "felt": 23, "fenc": [], "fernando": [], "fetch": [6, 15], "few": [1, 3, 4, 5, 9, 17, 18, 19, 25, 28], "fewer": [0, 9, 11, 19, 28, 31], "ff7b72": [], "ff9492": [], "ffa07a": [], "ffa657": [], "ffb757": [], "ffd700": [], "ffd900": [], "ffd9002e": [], "ffffff": [], "ffnn": [1, 12], "fi": [], "field": [0, 3, 6, 12, 19, 21], "fifth": [0, 6, 28], "fig": [0, 1, 2, 3, 4, 6, 7, 12, 13, 14, 23, 28], "fig_id": [0, 6, 7, 9, 28], "figaxi": 25, "figsiz": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 28], "figur": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 21, 23, 28, 29, 30, 31], "figure_id": [0, 6, 7, 9, 28], "figurefil": [0, 6, 7, 9, 28], "file": [0, 4, 5, 6, 7, 9, 15, 20, 23, 28], "file_prefix": 4, "filenam": 28, "fill": [5, 9, 18, 29, 30], "filter": [3, 4], "final": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 20, 23, 24, 25, 26, 28, 30], "financ": 0, "find": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 21, 23, 25, 28, 29, 30, 31], "fine": [0, 14], "finish": [2, 20], "finit": [3, 5, 6, 12, 13, 17, 25, 29, 30], "finnicki": 15, "first": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 19, 22, 23, 25, 26, 27, 29, 31], "first_moment": 31, "first_term": 31, "firsteigvector": 11, "fit": [1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 17, 18, 19, 23, 25, 29, 31], "fit_beta": 29, "fit_intercept": [0, 5, 6, 16, 29, 30, 31], "fit_mod": 9, "fit_theta": [6, 31], "fit_transform": [0, 6, 8, 9, 11, 15, 19], "fiti": [0, 28], "five": [0, 9, 28, 29], "fix": [0, 3, 4, 6, 10, 11, 12, 13, 23, 28], "flag": 4, "flat": [12, 13, 30, 31], "flatten": [1, 3, 4, 5, 22], "flavor": [], "flexibl": [1, 6, 8, 10, 12, 28, 31], "flip": [26, 28], "float": [0, 3, 4, 5, 9, 11, 13, 14, 22, 28, 29, 30], "float32": [4, 9], "float64": [4, 22, 28], "flop": [5, 22, 29, 30], "flow": [1, 4, 12], "fluctuat": [5, 31], "fly": 11, "fm": 0, "fmax": 3, "fmesh": 13, "fn": 7, "focu": [0, 3, 4, 5, 6, 15, 21, 23, 27, 28, 29, 30, 31], "focus": [1, 6, 7, 22, 29, 31], "fold": [6, 9, 23], "folder": [0, 4, 6, 15, 20, 23, 28], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31], "font": [7, 20, 25, 28], "fontdict": 25, "fontsiz": [1, 6, 8, 9, 10, 25], "fontweight": 1, "footprint": [3, 31], "foral": [8, 29], "forc": [0, 5, 6, 10, 11, 29, 30, 31], "forcast": 4, "forcier": [], "forecast": [4, 12], "forest": [0, 1, 9, 21, 28], "forget": [11, 31], "form": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 21, 22, 23, 25, 28, 29, 30, 31], "formal": [3, 4, 14, 18, 25], "format": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 20, 21, 25, 27], "format_data": 4, "formatstrformatt": [6, 13, 30, 31], "formatt": [], "formul": [4, 6, 11, 14], "formula": [3, 13, 25, 30], "forth": [4, 12], "fortran": [0, 21, 22, 28], "fortran2003": [21, 28], "fortran2008": 23, "fortran90": 25, "fortun": [0, 11, 29], "forward": [0, 3, 6, 21, 22, 28, 31], "found": [1, 2, 4, 5, 6, 12, 13, 19, 20, 23, 28, 29, 31], "foundat": [21, 28], "four": [4, 5, 6, 8, 12, 22, 24, 26, 28, 30], "fourier": [0, 28], "fourierdef1": 3, "fourierdef2": 3, "fourierseriessign": 3, "fourth": [12, 28, 29], "fp": 7, "frac": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 22, 23, 25, 28, 29, 30, 31], "fraction": 9, "frame": [7, 31], "framework": [1, 8, 10, 25], "frank": [5, 11], "frankefunct": [5, 6, 11], "fredli": [26, 28], "free": [0, 6, 11, 13, 15, 16, 18, 21, 22, 23, 25, 26, 27, 28], "freecodecamp": 21, "freedom": [5, 30], "freeli": [0, 23], "freez": 15, "frequenc": [3, 6, 7, 25], "frequent": [0, 8, 9, 13, 30], "frequentist": 21, "fresh": 10, "fridai": [15, 26, 28], "friedman": [6, 19, 23, 27, 28], "friendli": 4, "fro": 23, "frodo": 28, "frog": 3, "from": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27], "from_cod": 9, "from_logit": [3, 4], "from_tensor_slic": 4, "front": [0, 4, 5, 28, 29, 30], "frustrat": 15, "fulfil": [2, 5, 12, 29, 30], "full": [1, 3, 5, 7, 9, 10, 13, 25, 28, 29, 30], "full_matric": [5, 29, 30], "fulli": [3, 6, 12, 25], "fullnam": [], "fun": [21, 28], "func": 2, "function": [2, 3, 4, 5, 9, 14, 15, 16, 17, 18, 19, 20, 21, 22], "functionali": 11, "fundament": [0, 6, 21, 28], "funtion": 2, "furnish": [], "further": [2, 7, 9, 19, 28], "furthermor": [0, 3, 5, 6, 7, 11, 12, 13, 21, 23, 28, 29, 30, 31], "futur": [0, 4, 8, 9, 28], "fy": [15, 23, 24, 26, 27, 28], "fys4155": 23, "fys5419": [27, 28], "fys5429": [27, 28], "f\u00f8470": [26, 28], "g": [0, 1, 2, 3, 4, 6, 8, 9, 10, 11, 13, 15, 18, 19, 25, 28, 29, 30, 31], "g0": 2, "g_": [2, 9, 10, 31], "g_0": 2, "g_1": [2, 10], "g_2": [2, 10], "g_analyt": 2, "g_dnn_ag": 2, "g_euler": 2, "g_i": 2, "g_m": [3, 10], "g_n": 3, "g_re": 2, "g_t": [2, 31], "g_t_d2t": 2, "g_t_d2x": 2, "g_t_dt": 2, "g_t_hessian": 2, "g_t_hessian_func": 2, "g_t_jacobian": 2, "g_t_jacobian_func": 2, "g_trial": 2, "g_trial_deep": 2, "g_vec": 2, "gain": [1, 5, 7, 9, 10, 13, 29, 30], "galleri": [0, 28], "game": 4, "gamge": 28, "gamma": [0, 2, 8, 9, 10, 11, 13, 28, 30], "gamma1": 8, "gamma2": 8, "gamma_": [0, 28], "gamma_0": 10, "gamma_1": 10, "gamma_1x": 10, "gamma_i": [0, 8, 25, 28], "gamma_j": 13, "gamma_k": [13, 30], "gamma_m": 10, "gamma_x": [0, 28], "gap": [8, 31], "gate": [4, 12], "gather": [0, 1, 12, 29], "gaug": 12, "gaussbacksub": 22, "gaussian": [4, 5, 6, 8, 14, 18, 25, 28], "gaussian_point": 14, "gaussian_rbf": 8, "gave": [13, 31], "gavra": 28, "gbc": 28, "gca": [2, 6, 8, 13], "gd": [1, 30], "gd_clf": 10, "gdclassiffiercgain": 10, "gdclassiffierconfus": 10, "gdclassiffierroc": 10, "gdm": 13, "gdregress": 10, "ge": [1, 5, 7, 25, 29, 30], "gen_loss": 4, "gen_tap": 4, "gender": [0, 28], "genener": 4, "gener": [0, 1, 2, 3, 5, 6, 8, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 23, 25, 27, 29, 30, 31], "generaliz": 16, "generallay": 12, "generate_and_save_imag": 4, "generate_imag": 4, "generate_latent_point": 4, "generate_simple_clustering_dataset": 14, "generated_imag": 4, "generator_loss": 4, "generator_loss_list": 4, "generator_model": 4, "generator_optim": 4, "genom": 21, "geodes": 11, "geoff": 31, "geometr": [0, 13, 28, 31], "geometri": 5, "georg": 27, "geotif": 6, "geq": [2, 5, 8, 9, 13, 29, 30, 31], "geron": [0, 27, 28], "get": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 15, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31], "get_dummi": 9, "get_paramet": 2, "get_split": 9, "get_yaxi": 8, "get_yticklabel": 6, "gh": 15, "giant": 31, "gibb": [21, 28], "gif": 4, "gini": 10, "gini_index": 9, "ginvers": 13, "git": [0, 15, 21, 28], "gitcdn": [], "giter": [13, 31], "github": [0, 20, 21, 23, 24, 26, 27, 28, 29], "gitignor": 15, "gitlab": [0, 15, 21, 23, 28], "give": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 21, 23, 25, 28, 29, 30, 31], "given": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 22, 25, 28, 29, 30, 31], "global": [6, 7, 13, 30, 31], "glorot": 1, "gmail": [], "gnew": 13, "go": [0, 1, 3, 5, 6, 8, 9, 11, 12, 13, 15, 16, 18, 28, 29, 30], "goal": [0, 7, 9, 28], "goe": [0, 1, 2, 5, 6, 13, 14, 15, 19, 22, 28, 29, 30, 31], "goessner": [], "golden": 13, "gone": [5, 29, 30], "gong": 1, "good": [1, 3, 4, 5, 6, 9, 10, 11, 13, 15, 18, 21, 25, 27, 29, 30, 31], "goodfellow": [4, 27, 28, 29, 30], "googl": [1, 4, 21, 28], "got": [1, 6, 23], "gotten": 28, "gov": 6, "govern": 28, "gp": 27, "gpu": [1, 13, 21, 28, 31], "grad": [2, 13, 31], "grad_analyt": 13, "grad_ol": 18, "grad_ridg": 18, "grade": [23, 24], "gradient": [0, 3, 4, 7, 8, 9, 12, 21, 28, 29], "gradient_desc": 31, "gradientboostingclassifi": 10, "gradientboostingregressor": 10, "gradients_of_discrimin": 4, "gradients_of_gener": 4, "gradienttap": 4, "gradual": [1, 14], "grai": [4, 6], "granger": [], "grant": [], "graph": [1, 9, 11, 12, 13, 16, 20, 30, 31], "graph_from_dot_data": 9, "graphic": [0, 1, 9, 15, 28], "grasp": 0, "gray_r": [1, 3], "grayscal": 3, "great": [5, 13, 15, 30, 31], "greater": [1, 7, 25, 29], "greatli": 13, "greedi": 9, "green": [0, 3, 9, 25], "grei": 4, "grid": [1, 3, 6, 7, 8, 12, 25, 29, 31], "grossli": [13, 30], "ground": [0, 28], "group": [0, 6, 7, 9, 14, 15, 20, 21, 23, 24, 26, 28], "groupbi": [0, 28], "grow": [1, 3, 9, 10, 31], "growth": [0, 28], "gru": 4, "guarante": [0, 4, 13, 25, 28, 29, 30, 31], "guess": [1, 4, 10, 13, 14, 30, 31], "guestrin": 10, "gui": 15, "guid": 1, "guidelin": 20, "g\u00f6ssner": [], "h": [0, 1, 5, 6, 8, 13, 15, 19, 25, 26, 27, 28, 29, 30, 31], "h1": 2, "h_": [0, 13, 28, 30, 31], "h_0": 31, "h_1": [2, 13, 30], "h_2": [2, 13, 30], "h_m": 10, "h_t": 31, "ha": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 22, 23, 25, 28, 29, 30, 31], "haanen": [26, 28], "habit": [0, 29], "had": [0, 1, 6, 7, 13, 28, 30, 31], "hadamard": [1, 12, 13, 31], "half": [1, 8, 9], "halv": 10, "hand": [0, 1, 2, 3, 5, 11, 12, 13, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31], "handi": [3, 23], "handl": [0, 1, 2, 5, 9, 11, 15, 18, 21, 29, 30, 31], "handle_unknown": 9, "handsid": 12, "handwrit": 12, "handwritten": [1, 5], "happen": [1, 2, 3, 4, 5, 6, 10, 13, 25, 29, 30, 31], "hard": [1, 7, 8, 10, 13, 30, 31], "hardcopi": [21, 28], "harder": [0, 1, 19, 29], "harmon": 3, "hash": 31, "hasn": [], "hassl": [0, 21, 28], "hast": [21, 28], "hasti": [0, 6, 16, 17, 19, 20, 23, 27, 28, 29], "hat": [0, 1, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 18, 19, 22, 29, 30, 31], "hauser": [], "have": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31], "have_sys_un_h": [], "haven": 1, "he": 7, "head": [4, 10, 25], "header": [0, 28], "heads_proba": 10, "health": [0, 29], "hear": [0, 13, 28, 31], "heart": [0, 7, 28], "heatmap": [0, 1, 3, 7, 17, 20, 28], "heavi": 31, "heavili": 0, "heavisid": 1, "height": [1, 3, 6, 29], "held": [13, 31], "help": [0, 1, 4, 12, 13, 15, 16, 23, 28, 31], "helper": [4, 14], "henc": [0, 5, 6, 8, 9, 10, 12, 13, 28, 29, 30, 31], "henrik": [26, 28], "her": 7, "here": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "hereaft": [0, 8, 12, 28], "herebi": [], "hermitian": 22, "hessenberg": 22, "hessian": [0, 2, 5, 13], "heterogen": [9, 10], "hex": [], "hi": 7, "hidden": [1, 3, 4, 12], "hidden_bia": 1, "hidden_bias_gradi": 1, "hidden_layer_s": [0, 1, 28], "hidden_neuron": 4, "hidden_weight": 1, "hidden_weights_gradi": 1, "hierarch": [5, 29, 30], "high": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 13, 14, 21, 22, 23, 28, 29, 30, 31], "higher": [0, 1, 3, 5, 6, 8, 13, 18, 23, 28, 29, 30, 31], "highest": [1, 2], "highli": [0, 3, 4, 10, 19, 21, 22, 27, 28, 29, 30, 31], "highlight": [], "highwai": [], "hing": 8, "hint": [13, 15, 16, 29, 30], "hinton": 31, "hip": 21, "hire": 0, "hist": [4, 6, 7, 25], "histogram": [6, 7, 25], "histor": [7, 11], "histori": [3, 4, 12, 15, 31], "hitherto": 5, "hjorth": [26, 28, 29, 30, 31], "hobbi": 25, "hoc": [5, 29, 30], "hoff": 27, "hold": [1, 3, 6, 13, 14, 30, 31], "holder": [0, 28], "holdgraf_evidence_2014": [], "home": [], "homepag": [23, 28], "homework": [6, 13, 30, 31], "homogen": [1, 3, 9, 10, 13, 31], "honchar": 2, "hopefulli": [0, 11, 15, 19, 25, 28, 31], "horizont": 11, "horlyk": [26, 28], "hors": [3, 7, 28], "hot": [1, 9], "hour": [1, 21, 24, 25, 26, 28, 31], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 25, 28, 29, 30, 31], "href": [], "hspace": [0, 4, 8, 10, 25, 28], "hstack": 1, "htf": 28, "html": [0, 16, 20, 21, 23, 24, 26, 27, 28, 29, 30, 31], "http": [0, 3, 4, 6, 13, 15, 16, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31], "huang": [0, 28], "huber": [0, 28], "huge": [1, 3, 4, 21, 31], "human": [0, 1, 3, 6, 9, 12, 29], "humid": 9, "hundr": 1, "hungri": 1, "hybrid": 24, "hydrogen": [0, 28], "hyperbol": [1, 4, 12], "hyperparam": 8, "hyperparamet": [3, 4, 5, 6, 9, 13, 18, 23, 29, 30, 31], "hyperplan": 11, "h\u00f8rlyk": [26, 28], "i": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31], "i0": [0, 28], "i1": [0, 6, 8, 12, 28, 29, 31], "i2": [0, 8, 12, 28], "i3": [0, 12, 28], "i5": [0, 28], "i_": [13, 30, 31], "i_1": [5, 6], "i_2": [5, 6], "i_t": 31, "ian": 27, "ic": [1, 23], "id": [7, 13, 30, 31], "ida": [26, 28], "idea": [0, 1, 2, 3, 4, 6, 9, 10, 12, 13, 20, 22, 23, 29, 30, 31], "ideal": [0, 2, 6, 8, 13, 25, 28, 31], "idem": 6, "ident": [5, 6, 12, 13, 17, 18, 22, 29, 30], "identifi": [0, 1, 7, 9, 11, 12, 13, 14, 28, 29], "idx": [], "ieor": 25, "ifi": 27, "ifs": [21, 28], "ignor": [0, 1, 3, 9, 15, 29, 31], "ii": [22, 25], "iii": [22, 28], "ij": [0, 1, 3, 6, 8, 12, 14, 16, 22, 25, 28, 29, 31], "ik": [0, 22, 28, 29], "iki": [], "ill": 31, "illustr": [5, 7, 10, 12, 13, 14, 20, 21, 28], "ilsvrc": 31, "im": 6, "imag": [1, 3, 4, 6, 9, 11, 12, 14, 27, 28], "image_at_epoch_": 4, "image_batch": 4, "image_height": 3, "image_path": [0, 6, 7, 9, 28], "image_width": 3, "imageio": 6, "imagenet": 31, "images_from_seed_imag": 4, "imagin": 1, "immedi": [0, 3, 4, 6, 21, 28, 31], "implement": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 19, 20, 23, 25, 28, 29, 30, 31], "impli": [3, 5, 6, 7, 13, 22, 29, 30, 31], "implicit": [3, 31], "implicitli": [11, 25], "import": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 23, 25, 31], "importantli": 3, "importerror": [], "impos": [0, 6, 11, 12, 28], "imposs": [0, 5, 28, 29, 30], "impract": 31, "impress": [0, 12, 28], "improv": [0, 4, 5, 9, 10, 11, 13, 15, 23, 29, 30], "impur": 9, "imread": 6, "imshow": [1, 3, 4, 6], "in3050": [27, 28], "in3310": 28, "in4080": [27, 28], "in4300": [27, 28], "in4310": 27, "in5400": 3, "in5550": 27, "in_out_neuron": 4, "inaccur": [13, 30], "inact": 12, "inadequ": [0, 28], "inappropri": 31, "inch": [6, 29], "incident": [], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 15, 16, 17, 18, 19, 20, 21, 25, 26, 27, 28, 29, 30], "include_bia": [6, 9], "incom": [12, 16], "incorrect": 1, "incoveni": 8, "increas": [0, 1, 3, 4, 5, 6, 9, 12, 13, 19, 23, 25, 28, 29, 31], "increasingli": 25, "increment": 31, "ind": 6, "inde": [0, 2, 4, 5, 6, 13, 28, 29, 30], "indefinit": 4, "independ": [0, 5, 6, 7, 8, 12, 13, 25, 28, 29, 30, 31], "index": [0, 1, 3, 4, 10, 14, 21, 22, 23, 25, 27, 28], "index_col": [0, 28], "indic": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 16, 23, 28, 29], "indirect": [], "indispens": 6, "individu": [1, 6, 7, 10, 12, 25, 28, 29, 31], "indu": [], "indx": 22, "indx1": 2, "indx2": 2, "indx3": 2, "ineffici": [3, 13], "inequ": [8, 13], "inequaltii": 30, "inertia": 13, "inf1000": [21, 28], "inf1100": [21, 28], "inf1100l": [21, 28], "inf1110": [21, 28], "inf3000": 28, "infeas": [9, 31], "infer": [0, 1, 4, 6, 27, 28], "inferenc": 1, "infil": [0, 6, 7, 9, 28], "infin": [5, 6, 7, 11, 19, 29, 30], "infinit": [3, 31], "infinitesim": 25, "influenc": [6, 10, 18], "influenti": 1, "info": 28, "inform": [0, 1, 3, 4, 6, 9, 11, 12, 13, 14, 22, 23, 27, 28, 30, 31], "inforom": 15, "infrequ": 31, "infti": [3, 6, 13, 25, 30], "ingeni": [13, 30, 31], "ingredi": [0, 9, 28], "inher": [6, 31], "inherit": [22, 28, 31], "init": [], "initi": [0, 1, 2, 6, 10, 13, 14, 18, 22, 25, 28, 30, 31], "inject": 14, "inlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 25, 28, 29, 30, 31], "inner": [0, 13, 29], "innerhtml": [], "inp": 4, "inplac": 13, "input": [0, 1, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 23, 25, 28, 29, 30, 31], "input_dim": 1, "input_shap": [3, 4], "inputs": 1, "inputs_shuffl": [0, 1, 29], "inquiri": 20, "insert": [3, 5, 6, 8, 10, 25, 29, 30], "insid": [4, 7], "insight": [0, 1, 5, 21, 28, 29, 30], "insist": [6, 13, 29, 31], "inspir": [0, 1, 12, 23, 28], "instabl": 2, "instal": [0, 1, 5, 6, 9, 15, 20], "instanc": [0, 1, 2, 4, 6, 9, 11, 13, 16, 28, 29, 30, 31], "instanti": 10, "instead": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 17, 20, 22, 25, 28, 29, 31], "institut": 1, "instruct": [0, 1, 15], "int": [0, 1, 2, 3, 4, 5, 6, 11, 13, 14, 22, 25, 29, 31], "int32": 10, "int_": [3, 6, 25], "int_0": 25, "int_a": 25, "intak": [0, 29], "integ": [1, 2, 13, 14, 22, 25, 28], "integer_vector": 1, "integr": [3, 6, 25, 28], "intellig": [0, 14, 27, 28], "intend": 10, "intens": [1, 18], "intention": 14, "interact": [0, 6, 9, 12, 21, 23, 28], "intercept": [0, 6, 8, 11, 13, 16, 17, 18, 19, 28, 29, 30, 31], "intercept_": [0, 6, 8, 9, 13, 28, 29, 31], "interchang": [5, 12, 22], "interconnect": 1, "interesit": 19, "interest": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 21, 23, 25, 28, 29, 30], "interfac": [0, 1, 15, 22, 29], "interior": [0, 9, 28], "intermedi": [22, 29, 31], "intern": [1, 10, 12], "internation": [], "interpol": [1, 3, 4, 6, 12], "interpr": [5, 29, 30], "interpret": [0, 1, 6, 9, 10, 12, 13, 15, 16, 22, 23, 25], "interrupt": [], "interv": [0, 3, 5, 6, 7, 13, 19, 25, 28, 29, 30], "intial": [13, 30], "intract": [0, 4, 29], "intrins": [3, 11, 22, 25, 28], "intro": [21, 27, 28], "introduc": [0, 1, 5, 6, 8, 10, 12, 22, 23, 25, 28, 30, 31], "introduct": [1, 2, 4, 13, 27, 29, 30, 31], "introductori": [0, 4, 22, 27, 28, 29], "intuit": [0, 5, 6, 8, 12, 13, 23, 28, 31], "inv": [0, 5, 13, 17, 28, 29, 30, 31], "invalid": [], "invalu": [0, 13, 21, 28, 30], "invari": 1, "invd": 5, "inver": 8, "invers": [0, 3, 6, 13, 28, 29, 30, 31], "inverse_transform": 8, "invert": [0, 5, 7, 10, 13, 16, 18, 28, 31], "investig": [], "invh": [13, 31], "invok": 8, "involv": [0, 2, 6, 7, 11, 12, 28, 29, 31], "io": [0, 21, 23, 24, 26, 27, 28, 29], "ion": [], "ip": [0, 8, 25, 28], "ipca": 11, "ipynb": [21, 28], "ipython": [0, 5, 7, 9, 11, 14, 21, 23, 28, 29], "iq": 6, "iri": [8, 9], "irreduc": 6, "irrelev": [5, 29, 30], "irrespect": [0, 28], "irvin": 23, "isaac": [], "isaacmus": [], "iseffici": [], "isn": 5, "isnul": [], "isomap": 11, "issu": [1, 9, 15, 22, 31], "it_arrai": 13, "item": [0, 13, 28], "items": [22, 28], "iter": [1, 2, 4, 6, 8, 13, 14, 18, 23, 25, 30, 31], "its": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 21, 22, 23, 25, 28, 30, 31], "itself": [5, 6, 12, 19, 23, 25, 28, 29], "j": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 22, 23, 25, 27, 28, 29, 30, 31], "j1": 22, "j_": 6, "j_lasso_sk": 6, "j_ridge_sk": 6, "j_sk": 6, "jackknif": [6, 21, 28], "jacobian": [2, 13, 30], "janko": [], "jason": 4, "javascript": [], "jax": [21, 28, 31], "jeff": [], "jensen": [26, 28, 29, 30, 31], "jerom": [19, 23, 27], "jhauser": [], "ji": [12, 22], "jit": 13, "jj": [0, 5, 6, 28], "jk": [0, 1, 6, 12, 22, 28], "jl": [0, 28], "jm": 22, "jnp": 13, "job": [2, 8, 10, 15], "join": [0, 4, 6, 7, 9, 28], "joint": [4, 5], "jonathan": [], "json": [], "judg": [13, 30], "judgement": 6, "julia": [21, 22, 23], "jump": [25, 31], "junk": 4, "jupit": 28, "jupyt": [0, 15, 16, 19, 21, 23, 27, 28], "jupyterbook": [], "jupytext": [], "just": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 21, 25, 28, 29, 30, 31], "justif": 0, "justifi": [3, 10], "k": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 25, 26, 28, 29, 30, 31], "k0": 7, "k1": 7, "kaggl": [6, 23], "kappa_d": 25, "karl": [26, 28], "karush": 8, "katex": [], "katrin": [26, 28], "keep": [0, 1, 4, 5, 6, 11, 13, 14, 15, 18, 22, 23, 28, 29, 30, 31], "keepdim": [1, 6, 10, 22], "kei": [1, 3, 6, 12, 31], "kellei": [], "kenneth": [], "kept": [4, 6, 14], "kera": [0, 4, 21, 23, 28], "kernel": [0, 1, 3, 21, 28, 29], "kernel_regular": [1, 3], "kernel_s": 4, "kernelpca": 11, "kev": [0, 28], "kevin": [27, 28], "keyword": [18, 22, 28], "kfold": 6, "kg": 1, "ki": 22, "kick": [1, 13, 31], "kiener": 2, "kilomet": [6, 29], "kim": [], "kind": [0, 2, 3, 4, 8, 12, 13, 14, 28, 29], "kingma": 31, "kj": [6, 12, 22, 29, 31], "kjm": [21, 28], "kkt": 8, "kl": 25, "km": [12, 28], "kmean": 14, "kmeanspoint": 14, "kn_k": 14, "know": [0, 1, 2, 5, 6, 8, 13, 15, 16, 17, 19, 20, 21, 28, 29, 30], "knowledg": [0, 21, 28], "known": [1, 3, 4, 5, 6, 7, 8, 9, 12, 18, 22, 23, 25, 27, 29, 31], "kondev": [0, 28], "kp": 25, "kpca": 11, "kramdown": [], "kroneck": 14, "kt": [], "kuhn": 8, "kvalsund": [26, 28], "kwown": [0, 28], "l": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 22, 23, 25, 28, 30, 31], "l0": 7, "l1": [0, 1, 3, 7, 28], "l1_l2": [1, 3], "l1regl": 5, "l2": [1, 3], "l_": [22, 31], "l_1": 7, "l_2": [7, 13, 30, 31], "l_i": 31, "l_j": 12, "la": 13, "la_": [], "la_i": 12, "la_k": 12, "lab": [20, 21, 23, 28], "label": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 20, 21, 22, 23, 25, 28, 29, 30, 31], "labelencod": [7, 10], "labels": [6, 8, 9], "labels_shuffl": [0, 1, 29], "laboratori": 24, "lack": [0, 28, 31], "lagari": 2, "lagrang": [8, 11], "lam": 18, "lambda": [0, 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 17, 18, 19, 20, 23, 25, 28, 29, 30, 31], "lambda_": 11, "lambda_0": 11, "lambda_1": [5, 8, 11, 29, 30], "lambda_2": [8, 11], "lambda_i": [8, 11], "lambda_iy_i": 8, "lambda_jy_iy_j": 8, "lambda_k": 8, "lambda_n": [5, 8, 29, 30], "lamda": 1, "land": 8, "landmark": 8, "landscap": [13, 18, 30, 31], "langl": [0, 6, 11, 25, 28, 29], "languag": [0, 1, 4, 8, 21, 22, 23, 27, 28], "lapack": [22, 28], "laplac": 5, "laptop": [15, 21], "larg": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 13, 18, 21, 22, 23, 25, 27, 28, 29, 30, 31], "larger": [0, 3, 5, 6, 8, 10, 11, 13, 17, 25, 28, 29, 30, 31], "largest": [4, 8, 11], "lasso": [0, 7, 21, 28, 31], "lasso_sk": 6, "last": [0, 1, 3, 4, 5, 6, 7, 8, 12, 16, 17, 19, 22, 23, 25, 26, 28, 30], "latent": 4, "latent_dim": 4, "latent_point": 4, "latent_space_value_rang": 4, "later": [0, 1, 4, 7, 8, 12, 13, 14, 15, 19, 21, 23, 28, 31], "latest": [4, 15, 21], "latest_checkpoint": 4, "latex": [20, 28], "latexcodec": [], "latter": [0, 3, 6, 7, 8, 11, 13, 22, 25, 28, 29, 30, 31], "lattic": 12, "law": 0, "layer": [0, 4, 13, 28, 31], "lbfg": [7, 9, 10], "lc_messag": [], "lcc": [5, 6], "lda": 11, "ldot": [0, 6, 11, 23, 28], "le": [5, 7, 10, 13, 17, 25, 29, 30, 31], "lead": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 22, 25, 28, 29, 30, 31], "leaf": 9, "leaki": 1, "leakyrelu": 4, "lear": [13, 30], "learn": [3, 4, 5, 6, 7, 8, 9, 10, 12, 22, 26, 27], "learnabl": 3, "learner": 10, "learnig": 28, "learning_r": [8, 10], "learning_rate_init": [0, 1, 28], "learning_schedul": [13, 31], "learnt": 23, "least": [0, 7, 8, 10, 11, 17, 18, 21, 22, 25], "leat": [13, 31], "leav": [0, 1, 3, 5, 6, 9, 11, 28, 30], "lectur": [0, 1, 5, 10, 11, 12, 13, 21, 22, 23, 24, 26, 27, 29], "lecturenot": [0, 21, 23, 27, 28], "left": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 22, 23, 25, 28, 29, 30, 31], "leftarrow": [8, 12], "legend": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 15, 28, 29, 30, 31], "leinonen": 28, "len": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 17, 22, 28, 29, 30, 31], "length": [0, 1, 3, 4, 8, 9, 13, 16, 21, 28, 29, 30, 31], "length_of_sequ": 4, "leq": [0, 5, 7, 8, 13, 14, 25, 28, 29, 30, 31], "less": [0, 1, 3, 4, 5, 6, 8, 9, 13, 21, 25, 28, 29, 30, 31], "lessen": 1, "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 22, 25, 28, 29, 30, 31], "letter": [0, 16, 22, 25, 28, 29], "level": [0, 1, 5, 6, 9, 21, 22, 23, 24, 26, 28, 31], "leverag": 31, "lexer": [], "li": [8, 11], "liabil": [], "liabl": [], "lib": [], "liberti": 31, "liblinear": 10, "librari": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 22, 23, 25, 27, 29, 30, 31], "licenc": [], "licens": [0, 1, 21, 23, 28], "lie": [0, 6, 11, 25, 28, 29], "life": [0, 1, 8, 12, 28], "lifetim": 13, "light": [], "like": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 23, 25, 28, 29, 30, 31], "likelihood": [0, 1, 5, 9, 28, 29], "lim_": 25, "limit": [0, 5, 6, 8, 12, 22, 23, 28, 29], "lin_clf": 8, "lin_model": [], "lin_reg": 9, "linalg": [0, 2, 5, 6, 8, 11, 13, 17, 22, 25, 28, 29, 30, 31], "line": [0, 3, 6, 8, 11, 13, 15, 16, 20, 28, 30, 31], "line1": 8, "line2": 8, "line2d": [], "line3": 8, "line_model": 15, "line_ms": 15, "line_predict": 15, "linear": [1, 3, 5, 6, 7, 9, 10, 11, 12, 16, 17, 18, 19, 21, 23, 25, 31], "linear_model": [0, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 28, 29, 30, 31], "linear_regress": 6, "linearli": [5, 29, 30, 31], "linearloc": [6, 13, 30, 31], "linearregress": [0, 6, 7, 9, 15, 16, 19, 28, 29, 31], "linearsvc": 8, "lineat": 30, "liner": [1, 3], "linerar": 10, "linewidth": [0, 2, 4, 6, 8, 9, 10], "link": [0, 4, 9, 12, 15, 20, 21, 23, 24, 26, 28], "linlag": 5, "linpack": [22, 28], "linreg": [0, 28], "linspac": [0, 2, 3, 4, 6, 8, 9, 10, 13, 16, 17, 19, 22, 25, 28, 29, 31], "linu": 4, "linux": [0, 1, 21, 23, 28], "liquid": [0, 28], "list": [1, 2, 3, 4, 9, 15, 21, 23, 28, 31], "listedcolormap": [9, 10], "literatur": [1, 7, 14, 27], "littl": [1, 3, 9, 12, 31], "live": [8, 16], "ll": [0, 18, 25, 28, 29], "lle": [0, 29], "llm": 20, "lloyd": [4, 14], "lmb": [0, 2, 5, 6, 29, 30, 31], "lmbd": [0, 1, 3, 28], "lmbd_val": [0, 1, 3, 28], "lmbda": [13, 30, 31], "ln": [1, 13, 30], "load": [1, 4, 6, 7, 9, 10, 31], "load_boston": [], "load_breast_canc": [1, 7, 9, 10, 11], "load_data": [3, 4], "load_digit": [1, 3], "load_iri": [8, 9], "loc": [3, 6, 7, 8, 9, 10, 28], "local": [0, 1, 3, 7, 12, 13, 15, 29, 30, 31], "locat": [2, 3, 8, 15], "log": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 13, 15, 20, 22, 23, 28, 31], "log10": [0, 5, 6, 29, 30, 31], "log_": [0, 28], "log_clf": 10, "logarithm": [0, 5, 7, 17, 22, 28], "logbook": 23, "logic": [0, 1, 9, 28], "login": 15, "logist": [0, 1, 2, 8, 9, 10, 11, 12, 13, 21, 29, 30, 31], "logisticregress": [7, 9, 10, 11], "logit": 7, "logreg": [7, 9, 10, 11], "logspac": [0, 1, 3, 5, 6, 28, 29, 30, 31], "long": [0, 1, 3, 4, 12, 13, 28, 30, 31], "longer": [2, 3, 8, 10, 14, 22, 25, 28, 31], "loocv": 6, "look": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 20, 22, 23, 25, 28, 29, 30, 31], "loop": [1, 4, 6, 10, 12, 14, 16, 17, 18, 21, 22, 28, 31], "lose": 1, "loss": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 13, 18, 22, 23, 28], "loss_fil": 4, "lossfil": 4, "lost": 4, "lot": [1, 4, 6, 16, 19, 20, 31], "low": [0, 6, 9, 10, 11, 23, 28, 29], "lower": [0, 1, 3, 6, 9, 10, 16, 22, 29, 31], "lowercas": [22, 28], "lowest": [9, 13, 25, 31], "lr": [1, 3, 4, 10], "lstat": [], "lstm": 4, "lstm_2layer": 4, "lstsq": [0, 28, 29], "lt": 6, "lu": [0, 5, 28, 29, 30], "lubksb": 22, "luckili": 2, "ludcmp": 22, "lux": 22, "lvert": 1, "lw": [0, 28], "m": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 15, 22, 25, 26, 27, 28, 29, 30, 31], "m_": [9, 12], "m_0": 31, "m_1": 14, "m_h": [0, 28], "m_k": 14, "m_l": 12, "m_n": [0, 28], "m_p": [0, 28], "m_t": [13, 31], "ma": 11, "machin": [1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 15, 16, 22, 27, 29, 31], "machinelearn": [0, 6, 16, 20, 21, 23, 24, 26, 27, 28, 29, 30], "machineri": [], "mackai": 27, "macro": [], "made": [0, 1, 3, 4, 5, 6, 7, 9, 11, 12, 23, 28, 29, 31], "mae": [0, 28], "magic": 4, "magnitud": [1, 6, 7, 13, 29, 31], "mai": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 19, 21, 22, 23, 25, 28, 29, 30, 31], "mail": [24, 26], "main": [0, 1, 3, 4, 5, 6, 7, 9, 22, 23, 27, 29, 30, 31], "mainli": [0, 5, 6, 7, 9, 28, 29], "maintain": [6, 31], "major": [1, 6, 9, 10, 13, 22, 28, 30, 31], "make": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 18, 19, 21, 22, 23, 25, 27, 28, 30, 31], "make_axes_locat": 6, "make_moon": [8, 9, 10], "make_pipelin": [0, 6, 10, 29], "makedir": [0, 6, 7, 9, 28], "malcondit": 22, "malign": [1, 7, 9], "mammographi": 5, "manag": [0, 2, 3, 15, 21, 23, 28, 31], "mandatori": [26, 28], "mani": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30, 31], "manifold": 11, "manner": 3, "manual": [6, 29, 31], "map": [0, 1, 2, 6, 7, 8, 11, 12, 14, 25, 28], "marc": 29, "margin": [0, 5, 8], "marit": [0, 28], "mark": 28, "markdownfil": [], "markdownit": [], "markdownitdeflist": [], "markedli": [], "marker": [7, 22, 28], "markov": [21, 28], "markup": [], "marsaglia": 25, "mass": [0, 1, 5, 13, 29, 30], "massag": [0, 28], "masses2016": [0, 28], "masses2016ol": [0, 28], "masses2016tre": 0, "masseval2016": [0, 28], "master": [24, 26], "mat": [21, 28], "mat1100": [21, 28], "mat1110": [21, 28], "mat1120": [21, 28], "match": [1, 4, 5, 13, 14, 15, 29, 30, 31], "materi": [4, 5, 7, 13, 15, 22, 24, 26], "math": [3, 7, 12, 13, 22, 25, 27, 28, 31], "mathbb": [0, 4, 5, 6, 7, 8, 11, 12, 13, 14, 17, 19, 22, 23, 25, 28, 29, 30, 31], "mathbf": [0, 5, 6, 7, 8, 13, 19, 22, 23, 28, 29, 30, 31], "mathcal": [1, 5, 6, 7, 13, 23], "matheemat": 3, "mathemat": [0, 6, 11, 12, 13, 21, 22, 25, 27, 28, 31], "mathemati": 28, "mathrm": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 23, 25, 28, 29, 30, 31], "matmul": [1, 2, 5], "matnat": 27, "matplotlib": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 23, 25, 28, 29, 30, 31], "matric": [0, 1, 3, 4, 6, 7, 8, 11, 13, 16, 17, 21, 29, 30], "matrix": [0, 2, 3, 4, 6, 7, 8, 10, 13, 17, 18, 19, 23, 25], "matshow": 1, "matter": [2, 3, 13, 29, 30, 31], "matthia": [], "max": [0, 1, 2, 3, 4, 9, 10, 12, 13, 26, 28, 30, 31], "max_depth": [0, 9, 10], "max_diff": 2, "max_diff1": 2, "max_diff2": 2, "max_it": [0, 1, 8, 13, 28], "max_iter": 14, "max_leaf_nod": 10, "max_sampl": 10, "maxdegre": [0, 6, 10, 29], "maxdepth": 10, "maxim": [1, 4, 5, 7, 8, 11], "maximum": [0, 2, 3, 5, 7, 8, 9, 10, 13, 14, 28, 29, 30, 31], "maxpolydegre": [5, 6, 29, 30, 31], "maxpooling2d": 3, "mbox": [5, 6, 29, 30], "mcculloch": 12, "md": 11, "mdoel": 4, "me": [], "mean": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 25, 28, 31], "mean_absolute_error": [0, 28], "mean_divisor": 14, "mean_i": 25, "mean_matrix": 14, "mean_squared_error": [0, 4, 6, 7, 10, 15, 19, 28, 29], "mean_squared_log_error": [0, 28], "mean_vector": 14, "mean_x": 25, "meaning": [0, 4, 7, 28], "meansquarederror": [0, 28], "meant": [3, 7, 10, 13], "meanwhil": 31, "measur": [0, 1, 2, 5, 6, 9, 11, 12, 14, 16, 18, 19, 23, 25, 28, 29, 31], "mechan": [0, 4, 25, 28, 31], "median": [0, 28, 29, 31], "medicin": 12, "medium": [4, 8, 13, 31], "medv": [], "meet": [0, 26], "mehta": [0, 28, 29, 30], "member": 20, "memori": [3, 4, 11, 12, 13, 18, 22], "mentat": [], "mention": [0, 12, 13, 23, 25, 28, 30, 31], "merchant": [], "mere": [0, 23], "merg": [], "meshgrid": [2, 5, 6, 8, 9, 10, 11], "mess": 15, "messag": [5, 13], "messi": 2, "met": [0, 3, 8, 29], "meta": [], "meteorolog": 9, "meter": [6, 29], "method": [0, 1, 2, 3, 4, 5, 7, 8, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 25, 27, 29], "metion": 6, "metric": [0, 1, 3, 6, 7, 9, 10, 14, 15, 28, 29], "metropoli": [21, 28], "mev": [0, 25, 28], "mgd": [13, 31], "mglearn": [21, 28], "mgrid": 13, "mhjensen": [], "mi": 10, "mia": [26, 28], "michael": [], "microsoft": 27, "mid": 1, "midel": 4, "midnight": 15, "midpoint": 9, "might": [0, 1, 2, 4, 6, 9, 13, 15, 17, 18, 29, 30, 31], "migth": 17, "mild": 9, "millimet": [6, 29], "million": [0, 28, 29, 31], "mimic": 12, "min": [0, 2, 5, 8, 9, 30], "min_": [0, 2, 5, 14, 17, 28, 29, 30], "min_samples_leaf": 9, "mind": [0, 6, 13, 15, 18, 28, 29, 30, 31], "mindboard": 4, "mine": [21, 28], "mini": [1, 11, 12, 13, 30], "minibatch": [1, 11, 13], "minibathc": [13, 31], "miniforge3": [], "minim": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 29, 30, 31], "minima": [0, 1, 7, 13, 28, 30, 31], "minimum": [0, 1, 2, 6, 8, 9, 11, 13, 29, 30, 31], "minmaxscal": [0, 29, 31], "minor": 25, "minst": 1, "minu": 7, "mirjalili": 28, "mirror": 9, "misc": 6, "misclassif": [8, 9, 10], "misclassifi": [8, 10], "miser": 0, "mismatch": 1, "miss": [7, 10], "mistak": [4, 19], "mit": 27, "mitig": 31, "mix": [1, 2, 28], "mixtur": [13, 31], "mk": [9, 22], "mkdir": [0, 6, 7, 9, 28], "ml": [0, 1, 10, 13, 22, 23, 29, 30, 31], "mlab": 25, "mle": [5, 7], "mlp": 1, "mlpclassifi": 1, "mlpregressor": [0, 28], "mm": 22, "mml": 29, "mn": [12, 25], "mnist": [1, 11], "mo": [], "mod": 25, "mode": [24, 26, 28], "model": [2, 3, 5, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 20, 21, 23, 25, 27, 29, 30, 31], "model_select": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "moder": [10, 31], "modern": [0, 6, 7, 21, 28, 31], "modest": 31, "modif": [2, 12, 13], "modifi": [0, 1, 3, 5, 7, 8, 10, 12, 13, 28, 29, 30, 31], "modul": [0, 16, 22, 28], "modular": 25, "modulo": 25, "moe": [11, 29], "moment": [5, 6, 13, 25], "mondai": [26, 28], "monitor": [13, 31], "monoton": [5, 12, 25], "mont": [0, 6, 21, 25, 27, 28], "montli": 16, "moor": [5, 6], "more": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 25], "moreov": [0, 3], "morten": [26, 28, 29, 30, 31], "mortenhj": 28, "most": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 21, 23, 25, 28, 29, 30, 31], "mostli": [1, 11, 18, 31], "motion": [0, 13], "motiv": [1, 4], "moulin": 31, "move": [0, 4, 5, 6, 7, 9, 12, 13, 14, 15, 16, 23, 25, 29, 30], "mpl": [7, 28], "mpl_toolkit": [2, 6, 13, 30, 31], "mplot3d": [2, 6, 13, 30, 31], "mplregressor": 1, "mse": [0, 4, 5, 6, 9, 10, 15, 16, 17, 19, 20, 23, 28, 29, 30, 31], "mse_simpletre": 10, "mselassopredict": [5, 30], "mselassotrain": [5, 30], "mseownridgepredict": [6, 29, 30, 31], "msepredict": [5, 30], "mseridgepredict": [0, 5, 6, 29, 30, 31], "msetrain": [5, 30], "msg": [], "msle": [0, 28], "mt": [7, 12], "mu": [0, 6, 11, 13, 25, 28, 31], "mu0": 25, "mu1": 25, "mu2": 25, "mu_": [6, 25, 29, 31], "mu_i": [6, 29, 31], "mu_n": 11, "mu_x": 25, "much": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 20, 22, 23, 25, 28, 29, 30, 31], "multi": [0, 1, 3, 7, 21, 28], "multiclass": [1, 7], "multidimension": [11, 12, 28], "multilay": 1, "multinomi": 7, "multipl": [2, 4, 5, 6, 7, 12, 13, 15, 25, 29, 30, 31], "multipli": [3, 5, 6, 11, 13, 18, 22, 25, 29, 30, 31], "multiplum": 8, "multivari": [0, 2, 10, 11, 21, 25, 28], "multivariate_norm": [11, 14], "multpli": 16, "murphi": [11, 27, 28], "muse": [], "must": [1, 2, 5, 6, 8, 10, 12, 13, 14, 15, 20, 25, 29, 30, 31], "mutat": 7, "mutual": [1, 3, 6, 13], "mx_": 25, "my": 28, "myenv": [], "myriad": [0, 21, 28], "mz1": 25, "mz2": 25, "m\u00f8svatn": 6, "n": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "n1": 22, "n2": 22, "n8grai": [], "n_": [1, 2, 3, 8, 12, 25], "n_0": [12, 25], "n_boostrap": [6, 10], "n_bootstrap": 6, "n_categori": [1, 3], "n_cluster": 14, "n_compon": 11, "n_epoch": [13, 31], "n_estim": 10, "n_examples_to_gener": 4, "n_featur": [1, 18], "n_filter": 3, "n_hidden": 2, "n_hidden_neuron": [0, 1, 28], "n_i": 25, "n_input": [0, 1, 3, 29], "n_instanc": 9, "n_iter": 31, "n_job": 10, "n_k": 14, "n_l": [12, 25], "n_layer": 1, "n_m": 9, "n_neuron": 1, "n_neurons_connect": 3, "n_neurons_layer1": 1, "n_neurons_layer2": 1, "n_point": 14, "n_sampl": [6, 8, 9, 10, 14, 18], "n_split": 6, "n_step": 4, "n_t": 2, "n_x": 2, "nabla": [1, 13, 30, 31], "nabla_": [2, 13, 30, 31], "nabla_w": 13, "nag": 13, "naimi": [0, 28], "naiv": 7, "naive_kmean": 14, "name": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 18, 20, 21, 22, 23, 25, 26, 28, 29, 30], "namespac": [], "narrow": [13, 31], "nathaniel": [], "nation": [1, 5], "nativ": [21, 28], "natur": [0, 1, 4, 8, 9, 12, 13, 23, 25, 27, 28, 30, 31], "navier": 12, "navig": [15, 31], "nb": 25, "nb_": 22, "nbconvert": 28, "nd": 14, "ndarrai": 6, "ne": [9, 10, 22, 25, 29, 30], "nearest": [1, 3, 6, 11], "nearli": [13, 30], "neat": 28, "neccesari": 6, "necess": 2, "necessari": [0, 1, 3, 4, 8, 14, 18, 28], "necessarili": [0, 4, 11, 25, 28], "necesserali": 5, "neck": 7, "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 22, 25, 29, 30, 31], "neg": [0, 1, 3, 5, 6, 7, 10, 13, 22, 25, 28, 30], "neg_mean_squared_error": 6, "neglect": [25, 31], "neglig": 25, "neighbor": [3, 6, 11], "neither": [4, 13, 31], "neq": [13, 14, 25, 30], "nervou": 12, "nest": [9, 12], "nesterov": 13, "net": [2, 4, 12], "netlib": [22, 28], "network": [0, 9, 13, 21, 27, 29], "neural": [0, 13, 21, 27, 29], "neural_network": [0, 1, 2, 28], "neuralnetwork": 1, "neuron": [1, 2, 3, 4, 12], "neutral": [0, 28], "neutron": [0, 28], "never": [1, 4, 6, 9, 25], "new": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 20, 22, 28, 29, 30, 31], "new_chang": [13, 31], "new_hobbit": 28, "newaxi": [0, 3, 6, 9], "newli": [0, 28], "newlin": [], "newton": [1, 7, 8, 13, 25], "next": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 28, 29, 30, 31], "next_guess": 13, "next_input": 4, "ng": 1, "ni": 14, "nice": [0, 1, 5, 11, 28, 29, 30], "nicer": [18, 31], "nip": 31, "niter": [13, 30, 31], "nitric": [], "nlambda": [0, 5, 6, 29, 30, 31], "nlp": 27, "nm": 25, "nm_n": [0, 28], "nmse": 6, "nn": [2, 5, 6, 12, 22, 28], "nn_model": 1, "nnmin": 2, "node": [1, 3, 9, 10, 12], "nois": [0, 4, 5, 6, 8, 9, 10, 13, 18, 19, 23, 28, 29, 30, 31], "noise_dimens": 4, "noisi": [1, 6, 23, 31], "non": [0, 1, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 22, 25, 28, 29, 30], "nondifferenti": 31, "none": [0, 1, 2, 4, 5, 9, 10, 13, 25, 28, 29], "noninfring": [], "nonlinear": [3, 6, 8, 9, 11, 12], "nonneg": [6, 9, 13, 30], "nonparametr": 6, "nonsens": 25, "nonsingular": 22, "nonumb": [3, 7, 8, 13, 22], "nor": [1, 4, 13, 31], "norm": [0, 1, 5, 6, 8, 11, 13, 18, 28, 29, 30, 31], "normal": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "normali": [22, 28], "norwai": [6, 23, 28, 30, 31], "notat": [0, 2, 5, 6, 13, 14, 25, 28, 29, 30], "note": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 25, 27, 28, 31], "notebook": [0, 1, 3, 9, 15, 16, 19, 20, 21, 23, 28], "noteworthi": 31, "noth": [1, 2, 5, 8, 12, 14, 25, 29, 30], "notic": [4, 5, 12, 13, 22, 25, 28], "notion": 3, "novel": [3, 6, 10, 28], "novemb": [1, 26, 28], "now": [0, 2, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 19, 21, 22, 23, 25, 28, 29], "nowadai": [0, 1, 3, 9, 21, 28], "nox": [], "np": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 22, 25, 28, 29, 30, 31], "npm": [], "npr": 2, "nsampl": 6, "nt": 2, "nu": 25, "nuclear": [5, 29, 30], "nuclei": [0, 25, 28], "nucleon": [0, 28], "nucleu": [0, 28], "num": 4, "num_coordin": 2, "num_hidden_neuron": 2, "num_it": [2, 18], "num_neuron": 2, "num_neurons_hidden": 2, "num_point": 2, "num_tre": 10, "num_valu": 2, "number": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 22, 23, 24, 26, 28, 30], "numberid": 7, "numberparamet": 3, "numer": [0, 5, 6, 9, 10, 11, 12, 13, 21, 22, 27, 28, 29, 30, 31], "numpi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 23, 25, 29, 30, 31], "numpydocstr": [], "nunmpi": [5, 29], "nve_frngahw": 30, "nx": 2, "ny": 25, "o": [0, 1, 4, 5, 6, 7, 8, 9, 11, 22, 26, 27, 28, 29, 30, 31], "obei": [6, 11, 13, 29, 31], "object": [0, 1, 4, 8, 10, 15, 19, 22, 28, 31], "obliqu": [5, 29, 30], "observ": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 25, 28, 30, 31], "obtain": [0, 1, 5, 6, 7, 8, 9, 10, 12, 13, 14, 17, 22, 23, 25, 28, 29, 30, 31], "obviou": [5, 6, 11, 25, 29, 30], "obviouli": 28, "obvious": [0, 4, 5, 6, 22, 28], "oc": [29, 30], "occupi": [], "occur": [0, 6, 8, 9, 22, 25, 28], "octob": [26, 28], "od": 0, "odd": [0, 3, 7, 28, 29, 31], "odenum": 2, "odesi": 2, "oen": 0, "off": [1, 3, 4, 5, 9, 13, 20, 25, 31], "offer": [6, 11, 21, 22, 24, 26, 28], "offic": [26, 28], "offici": [24, 28], "often": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "ofter": [22, 28], "ol": [0, 13, 17, 19, 29, 31], "old": [1, 5, 10, 13, 15, 18], "ols_paramet": 16, "ols_sk": 6, "ols_svd": 6, "olsbeta": 30, "olstheta": [0, 5], "omega": [2, 3, 6], "omega_0": 3, "omit": [0, 5, 28, 29, 30], "onc": [1, 6, 9, 11, 13, 20], "one": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 19, 20, 21, 22, 23, 25, 26, 28, 29, 31], "onehot": 1, "onehot_vector": 1, "onehotencod": 9, "ones": [0, 2, 5, 6, 8, 9, 10, 11, 13, 16, 18, 22, 23, 28, 29, 30, 31], "ones_lik": 4, "ong": 29, "onl": 3, "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 22, 23, 25, 28, 29, 30, 31], "onlin": [11, 15, 20, 24, 31], "onto": [5, 11, 29, 30], "open": [0, 1, 4, 6, 7, 9, 15, 21, 23, 24, 26, 28], "oper": [0, 1, 3, 5, 6, 10, 11, 12, 13, 15, 16, 21, 25, 28, 29, 30, 31], "operation": 25, "oplu": 25, "opmiz": [13, 31], "opportun": 0, "oppos": [6, 13], "opposit": [1, 5, 8, 29, 30], "opt": [1, 5, 23, 28, 30], "optim": [0, 2, 3, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 19, 23], "optimis": [1, 3], "option": [0, 1, 3, 5, 6, 8, 11, 15, 18, 22, 29, 31], "optmiz": [1, 8, 13, 29], "oral": 28, "orang": 0, "order": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 15, 19, 22, 23, 25, 28, 29, 30], "ordinari": [0, 2, 3, 7, 11, 13, 17, 18, 21], "oreilli": [27, 28], "org": [0, 3, 4, 16, 20, 21, 22, 23, 27, 28, 29, 30, 31], "organ": [6, 7, 10, 22], "orient": [1, 5, 25, 29, 30], "origin": [0, 3, 5, 6, 8, 11, 12, 13, 15, 22, 28, 29, 30, 31], "orthogn": [5, 29, 30], "orthogon": [0, 5, 6, 8, 11, 13, 22, 28, 29, 30], "orthonorm": [5, 29, 30], "os": [26, 28], "oscar": 1, "oscil": [3, 13, 31], "oskar": 28, "oskarlei": 28, "osl": 18, "oslo": [0, 21, 23, 24, 26, 28, 29, 30, 31], "osx": [0, 21, 23, 28], "other": [0, 1, 2, 3, 5, 6, 7, 8, 10, 13, 14, 16, 19, 21, 24, 25, 26, 27, 29, 30, 31], "otherwis": [0, 1, 4, 7, 13, 22, 28, 31], "ouput": [5, 7, 12], "our": [1, 2, 3, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 19, 21, 22, 25, 31], "ourmodel": 0, "ourselv": [0, 5, 6, 8, 11, 13, 28, 29, 30], "out": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 21, 22, 23, 25, 28, 29, 31], "out_fil": 9, "outcom": [0, 7, 9, 10, 12, 25, 29], "outdoor": 9, "outer": [6, 12, 13], "outfil": 4, "outlier": [0, 8, 28, 29, 31], "outlin": [6, 10, 11], "outlook": 9, "outperform": [10, 31], "output": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 22, 23, 25, 28, 29, 30, 31], "output_bia": 1, "output_bias_gradi": 1, "output_shap": 4, "output_weight": 1, "output_weights_gradi": 1, "outputlayer1": 12, "outputlayer2": 12, "outsid": 4, "over": [0, 1, 3, 4, 5, 6, 9, 10, 12, 13, 15, 16, 19, 22, 23, 28, 29, 30, 31], "over1": 13, "overal": [1, 10, 31], "overcast": 9, "overcom": [12, 13], "overdetermin": [0, 28], "overfit": [0, 1, 3, 6, 9, 10, 13, 31], "overflow": [5, 31], "overhead": 12, "overlap": [3, 7, 8, 9], "overleaf": 20, "overlin": [0, 5, 6, 9, 10, 11, 14, 22, 28, 29, 31], "overshoot": 31, "overst": 0, "overtrain": 4, "overview": [3, 20], "own": [4, 5, 6, 8, 12, 13, 16, 18, 21, 22, 30, 31], "owner": [], "ownmsepredict": 0, "ownmsetrain": 0, "ownridgebeta": 29, "ownridgetheta": [0, 6, 29, 30, 31], "ownypredictridg": 0, "ownytilderidg": 0, "oxid": [], "p": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 22, 25, 28, 29, 30, 31], "p0": 2, "p1": 2, "p_": [2, 4, 8, 9], "p_hidden": 2, "p_i": [5, 25], "p_j": 25, "p_n": 25, "p_output": 2, "p_x": 25, "pack": [0, 28], "packag": [0, 1, 3, 4, 5, 8, 11, 13, 15, 20, 21, 23, 25, 29, 30, 31], "packtpub": 28, "packtpublish": 28, "pad": [3, 4], "page": [0, 21, 28, 30, 31], "pai": [0, 1, 9, 13, 15, 31], "pair": [0, 2, 3, 9, 21, 25, 28], "paltform": 15, "panda": [0, 4, 5, 6, 7, 9, 11, 21, 23, 30, 31], "pandoc": [], "panel": 28, "paper": [1, 31], "paper_fil": 31, "paradigm": [0, 28], "paragraph": 20, "parallel": [10, 13, 21, 22, 28], "param": 2, "paramat": 2, "paramet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, 18, 19, 23, 25, 30, 31], "parameter": [0, 6, 10, 28, 29], "parametr": [0, 6, 28, 29], "paramt": [3, 5], "parser": [], "part": [0, 1, 3, 5, 6, 10, 17, 19, 20, 22, 24, 25, 26, 28, 29], "partial": [0, 1, 5, 6, 7, 8, 10, 11, 12, 13, 16, 25, 28, 29, 30, 31], "particip": [15, 21, 24, 26, 28], "particl": [0, 4, 13, 25, 28], "particular": [0, 1, 2, 3, 5, 6, 9, 10, 11, 12, 13, 16, 23, 25, 27, 28, 29, 30, 31], "particularli": [5, 6, 8, 11, 13, 25, 29, 30, 31], "partit": [1, 4, 9], "partli": [6, 28], "partner": 15, "pass": [2, 3, 12, 14, 31], "password": 23, "past": [10, 25, 31], "patch": [6, 25], "path": [0, 4, 6, 7, 9, 21, 28, 31], "pathcollect": 17, "patholog": [], "patient": 7, "patter": 4, "pattern": [0, 3, 4, 12, 27, 28, 31], "pauli": [0, 28], "pav": [], "pc": [11, 15, 21], "pca": [0, 7, 21, 28, 29], "pd": [0, 4, 5, 6, 7, 9, 11, 28, 29, 30, 31], "pde": 2, "pdf": [0, 3, 4, 5, 6, 9, 15, 16, 19, 20, 23, 27, 28], "pedagog": [0, 28, 29], "penal": [6, 18, 29, 31], "penalti": [6, 13, 18, 23, 29, 31], "penros": [5, 6], "pentagon": [13, 30], "peopl": [1, 9, 13, 21, 31], "per": [0, 1, 6, 24, 26, 28, 31], "percentag": [10, 11, 26], "perceptron": [0, 1, 7, 28], "peregrin": 28, "perez": [], "perfect": [0, 1, 13, 28, 31], "perfectli": [4, 6], "perform": [0, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "performac": 4, "perhap": [0, 5, 13, 28, 29, 30, 31], "perimet": 1, "period": [1, 4, 25], "permiss": 15, "permit": [], "permut": 11, "persist": 13, "person": [5, 6, 7, 16, 20, 24, 26, 28, 29], "perspect": 27, "pertin": [12, 28], "petal": [8, 9], "peter": [27, 29], "phantom": 25, "phase": [6, 12], "phenomena": 25, "phenomenon": 31, "phi": 8, "phi_k": 8, "philipp": [], "philosophi": 13, "phone": [26, 28], "photo": [4, 28], "php": 23, "phrase": [0, 28], "physic": [0, 1, 4, 7, 12, 13, 25, 26, 27, 28, 29, 30, 31], "pi": [2, 3, 5, 6, 7, 9, 12, 13, 25], "pick": [1, 9, 10, 11, 13, 14, 31], "pickl": 1, "pictur": [0, 28], "pie": [21, 28], "piec": [11, 14], "pillow": [0, 21, 23, 28], "pinv": [5, 6, 13, 23, 29, 30, 31], "pip": [0, 1, 15, 21, 23, 28], "pip3": [0, 1, 23, 28], "pipelin": [0, 6, 8, 10, 29], "pippin": 28, "pit": 4, "pitfal": [6, 29], "pitt": 12, "pixel": [1, 3, 4, 28], "pixel_height": [1, 3], "pixel_width": [1, 3], "pkg_resourc": [], "pkgutil": [], "place": [0, 4, 6, 8, 13, 15, 22, 23, 28, 30], "plai": [0, 3, 4, 5, 6, 8, 11, 18, 21, 23, 28, 29, 30], "plain": [8, 10, 12, 13, 14, 30, 31], "plan": [6, 9, 26, 27, 28], "plane": [8, 9], "plateau": [5, 30, 31], "platform": [21, 28], "plausibl": 12, "pleas": [13, 23, 26, 28], "plenti": 1, "plethora": [3, 12], "plot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "plot_all_sc": [23, 29], "plot_confusion_matrix": [7, 10], "plot_count": 6, "plot_cumulative_gain": [7, 10], "plot_data": 1, "plot_dataset": 8, "plot_decision_boundari": [9, 10], "plot_import": 10, "plot_max": 4, "plot_min": 4, "plot_model": 4, "plot_numb": 4, "plot_predict": 8, "plot_regression_predict": 9, "plot_result": 4, "plot_roc": [7, 10], "plot_surfac": [2, 6, 13], "plot_train": 9, "plot_tre": [9, 10], "plt": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 22, 25, 28, 29, 30, 31], "plu": [0, 3, 5, 7, 18, 28, 29], "plugin": [], "pm": 8, "pmatrix": 2, "pml": 27, "pn": 3, "png": [0, 4, 6, 7, 9, 28], "point": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 20, 22, 23, 25, 26, 28, 29, 30, 31], "point_1": 4, "point_2": 4, "poisson": [21, 25, 28], "poli": [6, 8], "poly100_kernel_svm_clf": 8, "poly3": 0, "poly3_plot": 0, "poly_featur": [8, 9, 15], "poly_features10": 9, "poly_fit": 9, "poly_fit10": 9, "poly_kernel_svm_clf": 8, "poly_model": 15, "poly_ms": 15, "poly_predict": 15, "polydegre": [0, 5, 6, 10, 29], "polygon": [13, 30], "polym": 12, "polymi": 23, "polynomi": [0, 5, 6, 7, 8, 9, 10, 11, 15, 17, 19, 20, 23, 28, 29, 31], "polynomial_featur": [6, 15, 16, 17], "polynomial_svm_clf": 8, "polynomialfeatur": [0, 6, 8, 9, 15, 16, 19, 29], "polytrop": [0, 6], "pool": 3, "pool_siz": 3, "poor": [1, 13, 30, 31], "poorli": [0, 29], "popul": [0, 5, 28, 29], "popular": [0, 1, 3, 6, 7, 8, 9, 11, 12, 15, 21, 22, 23, 25, 29], "popularli": [0, 28], "portabl": 10, "portion": [11, 13, 31], "pose": [0, 4, 5, 6, 11, 25, 28], "posit": [0, 1, 2, 3, 5, 7, 8, 10, 11, 13, 14, 22, 25, 28, 29, 30, 31], "possibl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 23, 25, 26, 28, 29, 30, 31], "possibli": [6, 8, 13, 23], "post": [], "posterior": 5, "postpon": [0, 29], "postscript": 23, "postul": 5, "potenti": [0, 3, 5, 6, 12, 13, 29, 31], "pott": 12, "power": [0, 1, 5, 6, 8, 9, 12, 13, 28, 29, 30, 31], "pp": [5, 6, 19], "practic": [0, 5, 6, 7, 8, 16, 18, 19, 23, 25, 29], "practition": [0, 1, 3, 28, 31], "pre": 28, "preambl": [], "preced": [1, 11, 12, 25], "preceed": 4, "preceq": 8, "precis": [0, 2, 5, 11, 13, 22, 23, 25, 28, 29, 31], "pred": 6, "predicit": 0, "predict": [0, 1, 5, 6, 7, 8, 9, 10, 15, 16, 17, 19, 21, 23, 27, 28, 29, 30, 31], "predict_prob": 1, "predict_proba": [7, 10], "predictor": [0, 5, 6, 7, 9, 10, 11, 28, 29, 31], "prefer": [0, 1, 6, 8, 9, 11, 13, 15, 20, 21, 23, 28], "prepar": [0, 6, 22, 23, 28, 29], "preprocess": [0, 4, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 23], "prerequisit": 0, "prescript": 23, "presenc": 13, "present": [0, 5, 6, 7, 9, 12, 13, 22, 23, 25, 28, 29, 30, 31], "preserv": [3, 11, 22], "press": [13, 15, 27, 30], "pretrain": [1, 4], "pretti": [0, 4, 8, 9, 21, 23, 28], "prettier": [], "prev_centroid": 14, "prevent": [13, 25, 31], "previou": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 22, 23, 25, 29, 30, 31], "previous": [2, 3, 9, 10, 25], "price": [0, 4, 9, 13, 31], "primal": 8, "primari": [0, 7, 28], "prime": 25, "princip": [0, 5, 7, 21, 28, 29, 30], "principl": [0, 6, 7, 8, 14, 28], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 22, 25, 28, 29, 30, 31], "print_funct": [8, 9], "printout": [0, 28], "prior": [0, 5, 6, 28], "privat": 0, "prob": [1, 25], "probabilist": [0, 27, 28, 29], "probabl": [0, 1, 3, 4, 6, 7, 10, 13, 21, 28, 29, 31], "problem": [0, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 19, 21, 22, 23, 25], "probml": 27, "proce": [0, 5, 6, 7, 8, 9, 10, 11, 13, 22, 28, 29], "procedur": [2, 4, 5, 6, 8, 10, 11, 13, 29, 30, 31], "proceed": 22, "process": [0, 2, 4, 6, 9, 10, 12, 13, 21, 22, 23, 25, 27, 28, 30, 31], "procur": [], "prod": 27, "prod_": [1, 5, 7], "produc": [0, 3, 4, 5, 6, 9, 10, 11, 12, 13, 18, 20, 21, 22, 25, 28, 29], "product": [0, 1, 3, 5, 6, 7, 8, 12, 13, 16, 17, 21, 22, 28, 29, 31], "profess": [0, 28], "profit": [], "program": [0, 1, 4, 5, 6, 8, 12, 14, 15, 21, 22, 24, 25, 26, 28, 29], "programm": 22, "progress": [1, 4, 14, 31], "prohibit": 6, "project": [0, 1, 2, 3, 5, 11, 13, 15, 19, 21, 24, 29, 30, 31], "project_root_dir": [0, 6, 7, 9, 28], "promin": 12, "promis": 8, "promot": [26, 28], "prompt": 20, "prone": [9, 15], "pronounc": [13, 21, 28, 31], "proof": [0, 11, 12, 13, 28, 30], "prop": 31, "prop_cycl": [], "propag": [2, 3, 13, 31], "proper": [0, 2, 6, 7, 20], "properli": [1, 6, 8, 10, 13, 18, 20, 23, 31], "properti": [0, 1, 3, 12, 13, 16, 22, 28], "proport": [0, 1, 5, 9, 11, 13, 25, 28, 29], "propos": [1, 4, 6, 10, 23, 28, 31], "propto": [5, 13, 30, 31], "proton": [0, 28], "prove": [3, 13, 30, 31], "provid": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 20, 21, 22, 23, 25, 28, 29, 30, 31], "proxi": [1, 13, 31], "prune": 9, "pseudo": [22, 25, 31], "pseudocod": 23, "pseudoinv": 5, "pseudoinvers": [5, 6, 23], "pseudorandom": [6, 25], "psychologi": [0, 28], "pt": 13, "public": [0, 15, 21, 28], "publish": [], "pull": 15, "punish": [0, 1, 28], "pure": [3, 9, 25], "purest": 9, "puriti": 9, "purpos": [0, 3, 10, 12, 14, 28], "push": 15, "put": [1, 20, 31], "py": 5, "pybtex": [], "pycod": 28, "pydata": 21, "pydevd_extension_api": [], "pydevd_plugin": [], "pydevd_plugin_plugin_nam": [], "pydot": 9, "pygment": [], "pyhton2": 28, "pylab": [7, 28], "pypi": 21, "pyplot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 22, 25, 28, 29, 30, 31], "pythagora": 5, "python": [1, 2, 3, 5, 6, 8, 11, 12, 13, 14, 18, 20, 23, 25, 29, 31], "python2": [0, 23], "python3": [0, 21, 23, 28], "pythonpath": [], "pytorch": [0, 21, 23, 28], "pyzmq": [], "q": [5, 6, 8, 11, 25], "qp": 8, "qquad": [2, 11, 13, 22, 31], "qr": [5, 6, 22, 29, 30], "quad": [1, 13, 22], "quadrat": [0, 8, 9, 13, 28], "qualit": [4, 9, 23, 25], "qualiti": [0, 9, 21, 28, 29], "quantifi": 1, "quantil": 10, "quantit": [0, 6, 9, 23, 28], "quantiti": [0, 2, 5, 6, 7, 9, 10, 11, 12, 14, 16, 22, 25, 28, 29, 30, 31], "quantum": [4, 12, 27, 28], "quartil": [0, 29, 31], "quench": 5, "queri": 9, "question": [0, 5, 6, 9, 11, 12, 13, 23, 26, 28, 29, 31], "qugan": 4, "quick": [4, 25], "quicker": 31, "quickli": [1, 3, 9, 11, 13, 30, 31], "quit": [1, 5, 6, 9, 10, 12, 15, 29, 30], "quot": 4, "r": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 21, 22, 23, 25, 29, 30, 31], "r2": [0, 5, 6, 19, 28, 29, 30], "r2_score": [0, 28], "r2score": [0, 28], "r_": 31, "r_0": 31, "r_1": 9, "r_2": 9, "r_j": 9, "r_m": 9, "r_t": 31, "rad": [], "rade": [], "radial": [8, 12], "radioact": 25, "radiu": [0, 1, 29, 31], "radziej": [], "ragan": [], "rain": 9, "ram": 31, "ramanujam": [], "ramp": 1, "ran0": 25, "ran1": 25, "ran2": 25, "ran3": 25, "rand": [0, 4, 5, 6, 9, 10, 13, 15, 19, 22, 28, 29, 30, 31], "randint": [6, 9, 13, 31], "randn": [0, 1, 2, 5, 6, 9, 11, 13, 15, 18, 28, 29, 30, 31], "random": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 28, 29, 30, 31], "random_forest_model": 10, "random_index": [13, 31], "random_indic": [1, 3], "random_st": [7, 8, 9, 10, 11], "randomforestclassifi": 10, "randomli": [1, 6, 9, 13, 14, 18, 30, 31], "rang": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 19, 22, 25, 28, 29, 30, 31], "rangl": [0, 6, 11, 25, 28, 29], "rangle_x": 25, "rank": [5, 29, 30], "rankdir": 4, "raphson": [1, 8, 13], "rapidli": [0, 31], "rare": [1, 13, 31], "raschka": [28, 29], "rasckha": 28, "rashcka": [30, 31], "rate": [1, 2, 3, 4, 8, 9, 10, 12, 13, 18, 30], "rather": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 25, 28, 29, 30], "ratio": [4, 7, 9, 10, 11], "rational": [0, 28], "ravel": [5, 6, 7, 8, 9, 10, 11, 13, 22], "raw": [3, 31], "rbf": [8, 11, 12], "rbf_kernel_svm_clf": 8, "rbf_pca": 11, "rc": 25, "rcond": [0, 28, 29], "rcparam": [1, 3, 7, 8, 9, 10, 25, 28], "re": [2, 4, 13, 15, 30], "reach": [1, 4, 5, 6, 9, 10, 12, 13, 14, 30, 31], "react": [], "read": [0, 2, 3, 4, 5, 6, 7, 8, 11, 12, 16, 17, 19, 20, 22, 23, 25, 27, 30], "read_csv": [0, 6, 7, 9], "read_fwf": [0, 28], "reader": [0, 6, 20, 22, 25, 28, 29, 31], "readi": [0, 1, 5, 6, 8, 10, 11, 12, 22, 28], "readili": 1, "readm": [15, 20], "readthedoc": 21, "real": [0, 1, 4, 7, 10, 11, 12, 16, 18, 19, 22, 29], "real_loss": 4, "real_output": 4, "realist": [8, 28], "realiti": 25, "realiz": [1, 12], "realli": [0, 1, 28], "rearrang": 13, "reason": [0, 1, 3, 4, 10, 13, 27, 28, 30, 31], "reassign": 1, "recal": [5, 6, 9, 10, 11, 12, 22, 25, 28, 29, 30, 31], "recast": 3, "receiv": [1, 3, 10, 12, 25], "recent": [0, 6, 13, 27, 31], "recept": [3, 12], "receptive_field": 3, "recip": [0, 6, 7, 22, 23, 28, 29], "reciproc": 5, "recogn": [0, 4, 5, 10, 28], "recognit": [0, 1, 3, 12, 27, 28], "recommen": 28, "recommend": [0, 2, 3, 4, 5, 6, 8, 13, 15, 19, 20, 21, 22, 23, 27, 30, 31], "reconsid": 9, "reconstruct": 11, "record": [10, 23, 24, 26, 28], "recreat": 15, "rectangl": [9, 13, 30], "rectangular": [5, 29, 30], "rectifi": [1, 3, 12], "recur": [0, 21, 28], "recurr": [0, 1, 21, 28], "recurs": [9, 21, 22, 28], "red": [0, 3, 4, 6, 8, 9, 31], "redefin": [0, 10, 28, 29, 30], "redefinit": 30, "redistribut": [], "reduc": [1, 3, 5, 6, 9, 10, 11, 13, 28, 30, 31], "reduct": [0, 10, 11, 21, 25, 28, 29], "reegress": 23, "ref": 20, "refer": [0, 1, 2, 3, 5, 6, 11, 12, 13, 14, 20, 22, 27, 28, 29, 30, 31], "referansestil": 20, "referenc": 2, "refin": 12, "refit": 6, "reflect": [0, 1, 4, 5, 23, 25, 28], "refresh": [21, 28], "refreshprogrammingskil": 28, "reg": [10, 11], "regard": [1, 9, 13], "regardless": [12, 16], "regexp": [], "regim": 31, "region": [3, 4, 6, 9, 12, 23, 31], "regist": [6, 25], "reglasso": [5, 30], "regr_1": [0, 9], "regr_2": [0, 9], "regr_3": [0, 9], "regress": [1, 8, 11, 12, 16, 20, 21, 22], "regressor": [0, 7, 10], "regret": [], "regridg": [0, 5, 6, 29, 30, 31], "regular": [0, 3, 4, 5, 6, 7, 9, 13, 17, 18, 26, 28, 29, 30, 31], "regularli": 15, "reilli": [0, 27, 28], "reinforc": [0, 8, 21, 28], "reiter": 1, "reitz": [], "reject": 7, "rel": [0, 4, 6, 7, 9, 12, 13, 25, 28, 29, 31], "relat": [0, 1, 3, 4, 5, 11, 13, 14, 19, 22, 25, 28, 29, 30], "relationship": [0, 4, 9, 18, 28], "relativeerror": [0, 28, 29], "releas": [1, 21, 28], "relev": [0, 1, 5, 7, 11, 21, 23, 25, 28, 30, 31], "reli": [0, 6, 8, 31], "reliabilti": 23, "reliabl": [7, 25], "relu": [3, 4, 28], "remain": [1, 2, 4, 6, 12, 22, 25, 29, 31], "remaind": 25, "reman": 2, "remark": 1, "rememb": [0, 8, 13, 20, 22, 23, 28, 31], "remind": [0, 5, 11, 13, 19, 22, 25], "remot": 15, "remov": [4, 5, 6, 18, 29, 30, 31], "renam": 15, "render": [0, 28, 29], "reorder": [5, 7, 29, 30], "reorgan": [0, 28], "repeat": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 14, 22, 23, 25, 28, 29, 30, 31], "repeated": 28, "repeatedli": [0, 6, 10, 13], "repet": 3, "repetit": [6, 28, 29], "rephras": [13, 30], "replac": [0, 1, 3, 4, 5, 6, 10, 12, 14, 21, 23, 28, 29, 30], "replica": 6, "repo": [15, 23], "report": [28, 31], "repositori": [4, 20, 23, 28], "reposotori": 20, "repres": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 23, 25, 28, 29, 30, 31], "represent": [0, 1, 3, 6, 25, 28], "representd": 3, "reproduc": [0, 5, 6, 9, 12, 15, 16, 18, 20, 21, 25, 28, 29], "repuls": [0, 28], "request": [0, 13, 31], "requir": [0, 1, 3, 4, 5, 6, 8, 9, 11, 12, 13, 15, 17, 18, 19, 20, 22, 28, 29, 30, 31], "res1": 2, "res2": 2, "res3": 2, "res_analyt": 2, "res_analytical1": 2, "res_analytical2": 2, "res_analytical3": 2, "resaml": 6, "resampl": [0, 7, 10, 21, 28, 29], "rescal": [0, 11, 12, 31], "rescu": 5, "reseach": 6, "research": [0, 4, 13, 21, 27, 28, 31], "resembl": [6, 25], "reserv": [1, 5, 6, 25], "reshap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 22, 28, 29], "resid": 31, "residenti": [], "residu": [0, 5, 13, 28], "resiz": [5, 29, 30], "resnet": 31, "resort": 31, "resourc": [28, 31], "respect": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17, 18, 23, 25, 28, 29, 30, 31], "respond": 12, "respons": [0, 7, 9, 12, 28, 29], "rest": [0, 5, 18, 29, 30, 31], "restat": [0, 12, 28], "restor": 4, "restored_discrimin": 4, "restored_gener": 4, "restrict": [0, 3, 9, 12, 28], "result": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 28, 31], "retail": [], "retain": [5, 6, 29, 30, 31], "return": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 22, 25, 28, 29, 30, 31], "return_data": 14, "return_sequ": 4, "return_x_i": 9, "reus": [1, 3, 6, 19, 20, 23], "reveal": [0, 12, 28], "revers": [1, 22], "review": [21, 22], "revis": [], "revisit": 14, "revolut": 28, "reward": [0, 4, 28], "rewrit": [0, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 19, 22, 23, 25, 30, 31], "rewritten": [2, 6, 8, 10, 25], "rewrot": 13, "rf": 10, "rgb": 3, "rgoj5yh7evk": 21, "rh": 6, "rho": [0, 10, 13, 31], "rho_1": 10, "rho_2": 10, "rho_m": 10, "rich": [0, 28], "ride": 9, "rideclass": 9, "ridedata": 9, "ridg": [7, 11, 13, 20, 21, 28], "ridge_paramet": 17, "ridge_sk": 6, "ridgebeta": 30, "ridgetheta": 5, "right": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 19, 22, 23, 25, 28, 29, 30, 31], "right_sid": 2, "rightarrow": [0, 1, 5, 6, 8, 11, 12, 13, 25, 28, 29, 30, 31], "rigor": [0, 28, 29, 30], "ring": 6, "rise": [0, 28], "risk": [0, 13, 28, 30, 31], "rival": 4, "river": [], "rlm": 28, "rm": [25, 31], "rmse": [], "rmsporp": [13, 31], "rmsprop": [1, 3, 4, 13, 23], "rnd_clf": 10, "rng": 25, "rnn": [4, 12], "rnn1": 4, "rnn2": 4, "rnn_2layer": 4, "rnn_input": 4, "rnn_output": 4, "rnn_train": 4, "rntrick1": 25, "rntrick2": 25, "rntrick3": 25, "rntrick4": 25, "ro": [0, 13, 28, 30, 31], "robert": [19, 23, 27], "robust": [0, 28, 31], "robustscal": [0, 29, 31], "roc": [7, 10], "role": [0, 2, 5, 6, 8, 18, 21, 23, 28, 29, 30, 31], "roll": 6, "ronach": [], "room": [0, 26, 28], "root": [0, 5, 9, 13, 15, 25, 29, 30, 31], "root_directori": [], "rot": 28, "rotat": [1, 8, 9, 10], "rotation_matrix": 9, "roughli": [1, 3, 18], "round": [7, 9, 13], "routin": [13, 22, 28, 30], "row": [0, 1, 2, 5, 6, 9, 11, 16, 22, 28, 29, 30], "rr": [5, 29, 30], "rrr": [5, 29, 30], "rubric": [], "rudg": [], "rug": [13, 30, 31], "rule": [0, 1, 5, 6, 13, 23, 28, 29, 30], "run": [0, 1, 2, 4, 5, 6, 8, 9, 11, 13, 15, 20, 21, 23, 28, 29, 30, 31], "runtim": [1, 6, 14, 15], "rust": [0, 21, 22, 28], "rvert": 1, "rvert_2": 1, "s_": [3, 6], "s_1": 6, "s_i": [6, 7], "s_j": 6, "s_k": 6, "s_phenomenon": 23, "saddl": [13, 30, 31], "safeguard": [18, 31], "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 22, 23, 25, 28, 29, 30, 31], "said": [6, 9, 13, 30], "sake": [0, 5, 7, 11, 28, 29, 30], "sale": [0, 28], "sam": 28, "same": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 18, 20, 22, 23, 25, 28, 29, 30], "samm": 10, "sampl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 14, 18, 19, 21, 22, 23, 25, 28, 29, 31], "sample_vari": 14, "sampleexptvari": 25, "samwis": 28, "sastri": 11, "satisfactori": [0, 28], "satisfi": [1, 2, 3, 6, 8, 13, 22, 25, 30], "satur": [1, 6], "save": [0, 4, 6, 7, 9, 13, 20, 28, 31], "save_fig": [0, 6, 7, 9, 10, 28], "savefig": [0, 4, 6, 7, 9, 25, 28], "savetxt": 4, "saw": [5, 29], "scalabl": 10, "scalar": [2, 5, 6, 10, 29], "scale": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 23, 26, 28, 30], "scale_mean": 4, "scale_std": 4, "scaler": [0, 7, 8, 9, 10, 11, 17, 23, 29], "scan": [5, 7], "scari": 5, "scatter": [0, 1, 6, 7, 8, 9, 14, 15, 17, 28, 29, 31], "scenario": [6, 13, 30, 31], "schedul": [13, 31], "scheme": [1, 13, 30, 31], "schrage": 25, "sch\u00f8yen": [6, 29, 31], "scienc": [0, 1, 10, 12, 13, 21, 24, 25, 26, 27, 30], "scientif": [0, 20, 21, 23, 28], "scientist": [0, 28], "scikit": [3, 5, 6, 8, 9, 10, 13, 15, 16, 20, 21, 22, 23, 27], "scikit_learn": 0, "scikitlearn": 28, "scikitplot": [7, 10], "scipi": [0, 3, 5, 6, 13, 21, 22, 23, 28, 29, 30], "scl": 6, "scm": 15, "score": [0, 1, 3, 6, 7, 9, 10, 11, 15, 16, 19, 23, 26, 28, 29, 31], "scores_kfold": 6, "scratch": [1, 13, 16], "script": [], "sdg": [13, 31], "sdv4f4s2sb8": [30, 31], "seaborn": [0, 1, 3, 6, 7, 28], "seamless": [0, 21, 23, 28], "search": [0, 1, 3, 5, 9, 13, 15, 28, 30, 31], "sebastian": 28, "sebastianraschka": 28, "sec": 6, "second": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 15, 16, 20, 21, 22, 25, 26, 28, 29, 30], "second_mo": 31, "second_term": 31, "secondari": 31, "secondeigvector": 11, "secondli": 12, "section": [4, 11, 16, 20, 22, 23, 25, 29, 31], "sector": 0, "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 18, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "seed": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 18, 20, 25, 28, 29, 30, 31], "seed_imag": 4, "seek": [1, 2, 8], "seem": [1, 3, 4, 31], "seemingli": [0, 28], "seen": [0, 1, 3, 5, 10, 12, 25], "segment": [13, 30], "seismic": 6, "seldomli": [0, 28], "select": [1, 5, 6, 8, 9, 10, 11, 15, 20, 23, 24, 25, 26, 27, 28, 29, 30, 31], "selevet": 15, "self": [1, 5, 29], "sell": 4, "semest": [7, 24], "semi": [8, 13, 30, 31], "semilogx": 6, "send": [5, 12, 13, 26, 28], "senior": [24, 26], "sens": [0, 4, 6, 8, 28], "sensibl": 3, "sensit": [0, 5, 6, 9, 13, 28, 29, 31], "sent": 2, "sentenc": [4, 12], "separ": [0, 1, 2, 4, 6, 8, 9, 12, 14, 18, 21, 23, 25, 28, 31], "septemb": [18, 23, 28], "sequenc": [3, 4, 7, 9, 10, 12, 13, 21, 22, 25, 28, 30], "sequenti": [1, 3, 4, 10, 12, 25], "seri": [0, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 22, 28, 29, 30], "serif": [7, 25, 28], "serv": [0, 1, 2, 3, 5, 7, 13, 27, 28, 29, 30, 31], "servic": 23, "session": [1, 15, 20, 23, 24, 26, 28], "set": [1, 4, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 18, 21, 22, 23, 25, 26, 31], "set_major_formatt": 6, "set_major_loc": 6, "set_tick": [1, 8], "set_ticklabel": 1, "set_titl": [0, 1, 2, 3, 7, 12, 14, 28], "set_xlabel": [0, 1, 2, 3, 7, 12, 28], "set_xlim": [7, 12], "set_xticklabel": 1, "set_ylabel": [0, 1, 2, 3, 7, 28], "set_ylim": [7, 12], "set_ytick": 7, "set_yticklabel": [1, 6], "set_zlim": 6, "seth": 4, "setminu": 6, "setosa": [8, 9], "setosa_or_versicolor": 8, "setp": 6, "setup": [1, 4, 6, 8, 21, 28, 29, 30], "sever": [0, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 21, 22, 23, 25, 28, 29, 30, 31], "sgd": [1, 3, 30], "sgd_clf": 8, "sgdclassifi": 8, "sgdreg": 13, "sgdregressor": 13, "sgn": [5, 29, 30], "shall": [], "shallow": [13, 31], "shape": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 22, 28, 29, 30, 31], "share": [1, 3, 15, 28], "shareabl": 15, "she": 7, "shibukawa": [], "shift": [1, 6, 12, 15, 18, 25, 29, 31], "ship": 3, "shire": 28, "short": [4, 5, 20, 23], "shortcom": [13, 30, 31], "shorten": 4, "shorter": 25, "shorthand": 28, "shortli": [22, 28], "should": [0, 2, 3, 5, 6, 8, 9, 11, 12, 15, 18, 19, 20, 22, 23, 25, 28, 29, 31], "show": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 22, 23, 25, 28, 29, 30, 31], "show_shap": 4, "shown": [0, 4, 5, 8, 12, 13, 22, 29, 30, 31], "shrink": [3, 5, 6, 8, 11, 29, 30, 31], "shrinkag": [5, 6, 29, 30], "shrunk": 11, "shuffl": [0, 1, 4, 6, 13, 29, 31], "side": [0, 2, 5, 8, 12, 13, 22, 23, 28, 30], "sigh": [21, 28], "sigma": [0, 1, 5, 6, 7, 10, 11, 12, 13, 19, 22, 23, 25, 28, 29, 30, 31], "sigma0": 25, "sigma1": 25, "sigma2": 25, "sigma_": [5, 22, 28, 29, 30], "sigma_0": [5, 29, 30], "sigma_1": [5, 29, 30], "sigma_2": [5, 29, 30], "sigma_fn": [7, 12], "sigma_i": [0, 5, 28, 29, 30], "sigma_j": [5, 29, 30], "sigma_m": [6, 25], "sigma_n": [11, 25], "sigma_t": 13, "sigma_x": 25, "sigmoid": [1, 2, 4, 7, 8, 10, 12], "sigmundson": [6, 29, 31], "sign": [1, 2, 7, 8, 10, 25, 26], "signal": [1, 3, 10, 12, 31], "signifi": 4, "signific": [1, 31], "significantli": [1, 13, 18, 25, 30, 31], "sim": [4, 5, 6, 13, 19, 25], "similar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 18, 21, 22, 23, 28, 30], "similarli": [0, 1, 3, 5, 8, 10, 13, 25, 28, 29, 30, 31], "simpl": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 14, 16, 17, 21, 22, 25], "simplepredict": 10, "simpler": [0, 1, 5, 6, 7, 13, 16, 21, 23, 28, 30, 31], "simplernn": 4, "simplest": [0, 1, 3, 4, 9, 10, 12, 14, 23, 28], "simpletre": 10, "simpli": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 21, 22, 23, 25, 28, 29, 30, 31], "simplic": [2, 5, 6, 7, 8, 9, 10, 11, 12, 14, 29, 30, 31], "simplicti": [5, 29, 30], "simplifi": [0, 6, 9, 18, 21, 23, 28, 29, 31], "simplist": [3, 6, 25], "simul": [6, 18, 31], "simultan": [6, 31], "sin": [0, 1, 2, 3, 4, 9, 12, 13, 22, 28], "sinc": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 16, 18, 22, 23, 25, 27, 28, 29, 30, 31], "sine": [3, 12], "singl": [0, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 18, 19, 22, 25, 28, 29, 30, 31], "singular": [0, 6, 13, 22, 28], "sinusoid": 3, "site": [0, 23, 24, 29], "situat": [0, 4, 5, 7, 13, 25, 28, 29, 30, 31], "six": [3, 25], "size": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 18, 20, 22, 23, 25, 28], "sizesp": 31, "sketch": 10, "ski": 9, "skill": 0, "skip": 11, "skl": [0, 6, 28, 29, 31], "sklearn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 19, 20, 28, 29, 30, 31], "skplt": [7, 10], "sl": [6, 29, 31], "slack": 8, "slender": [], "slice": [2, 22, 28], "slide": [0, 3, 16, 23, 25, 28, 29, 30], "slight": [6, 13], "slightli": [1, 2, 3, 5, 6, 7, 10, 25, 29, 30], "slope": [8, 11, 12], "slow": [0, 2, 8, 13, 18, 29, 30, 31], "slower": [5, 22, 28, 29, 30, 31], "slowest": 22, "slowli": [12, 31], "slp": 1, "small": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 18, 21, 22, 25, 28, 29, 30, 31], "smaller": [0, 1, 2, 5, 6, 8, 9, 11, 13, 25, 28, 29, 30, 31], "smallest": [0, 4, 14, 28], "smallest_row_index": 14, "smodin": [], "smooth": [0, 3, 6, 13, 23, 28, 30, 31], "smoother": 31, "sn": [0, 1, 3, 6, 7, 28], "sne": 11, "so": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31], "soar": 6, "social": 0, "soft": [1, 7, 10, 12], "soften": 8, "softmax": [3, 7], "softwar": [0, 8, 21, 22], "sokogskriv": 20, "sol": 8, "sole": [0, 6, 28], "solid": [0, 7], "solut": [0, 1, 2, 3, 5, 6, 8, 10, 11, 13, 18, 22, 23, 25, 28, 29, 30, 31], "solution_ev": 31, "soluton": 2, "solv": [0, 1, 3, 5, 6, 8, 10, 11, 12, 13, 16, 22, 23, 28, 29], "solve_expdec": 2, "solve_ode_deep_neural_network": 2, "solve_ode_neural_network": 2, "solve_pde_deep_neural_network": 2, "solveod": 2, "solveode_popul": 2, "solver": [2, 7, 8, 9, 10, 22, 28], "some": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 23, 25, 28, 31], "some_model": [6, 29, 31], "somehow": 4, "someon": 16, "someth": [0, 1, 3, 4, 7, 9, 11, 15, 19, 20, 23, 25, 28, 29], "sometim": [0, 1, 11, 12, 13, 14, 19, 29, 31], "soon": [22, 26, 29], "sophist": [0, 28], "sopt": 13, "sort": [5, 6, 9, 11, 25], "sound": [3, 5], "sourc": [0, 1, 3, 6, 21, 22, 23, 25, 28, 31], "space": [0, 1, 4, 5, 8, 9, 11, 12, 13, 14, 25, 29, 30, 31], "span": [0, 3, 5, 9, 11, 22, 28, 29, 30], "spare": 1, "spars": [3, 6, 18, 22, 28, 31], "sparse_mtx": [22, 28], "sparsecategoricalcrossentropi": 3, "sparsiti": [10, 18], "spatial": [1, 2, 3, 12], "speak": 25, "special": [6, 7, 10, 12, 13, 22, 25, 28, 29, 30, 31], "specif": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 15, 16, 21, 22, 23, 25, 27, 28, 29, 30], "specifi": [0, 3, 5, 6, 7, 9, 11, 13, 14, 25, 28, 30, 31], "specifici": [0, 10, 28], "spectacular": 3, "spectral": 1, "speech": [0, 1, 3, 4, 12], "speed": [1, 2, 4, 13], "spend": [16, 25, 31], "spent": 23, "sphere": [0, 29, 31], "sphinx": [], "sphinx_book_them": [], "sphinxcontrib": [], "spike": 31, "spin": 6, "spite": 0, "spitzer": [], "spline": 8, "split": [1, 3, 4, 5, 6, 8, 9, 10, 11, 14, 16, 17, 20, 23, 25, 28, 30, 31], "splite": 0, "splitter": [1, 10], "spoiler": [], "spontan": 25, "spot": 3, "spread": [0, 11, 25, 28, 29], "springer": [19, 23, 27, 28], "spuriou": [13, 31], "sqquar": 30, "sqrsignal": 3, "sqrt": [3, 4, 5, 6, 8, 10, 11, 13, 25, 29, 30, 31], "squar": [1, 2, 3, 4, 7, 8, 9, 11, 13, 14, 15, 17, 18, 21, 22, 25], "squarederror": 10, "squaredeuclidean": 14, "squash": 12, "src": [], "srtm": 6, "srtm_data_norway_1": 6, "stabil": [5, 23, 31], "stabl": [0, 4, 5, 6, 9, 16, 20, 21, 23, 28, 29, 30, 31], "stack": [3, 4], "stage": [5, 13, 15, 23, 31], "stagnat": 31, "stai": [0, 2, 4, 5, 11, 28, 29, 31], "stand": [0, 5, 9, 12, 28, 29, 30], "standard": [0, 1, 4, 5, 6, 7, 8, 10, 12, 17, 18, 19, 22, 23, 25, 28, 30, 31], "standardscal": [0, 6, 7, 8, 9, 10, 11, 17, 29, 31], "standpoint": 31, "stanford": [13, 30], "start": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 22, 25, 26, 28, 29, 30, 31], "start_tim": 14, "starter": [], "stat": 6, "state": [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 21, 25, 28, 29, 30], "statement": [0, 7, 22, 28], "static": [], "stationari": [30, 31], "statist": [0, 1, 3, 4, 7, 9, 10, 11, 12, 13, 14, 19, 22, 23, 27, 29, 30, 31], "statu": [0, 7, 15, 28], "stavang": 6, "stb": [], "std": [0, 4, 6, 18, 28, 29, 31], "steep": [13, 30, 31], "steepest": 31, "stefan": [], "step": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 22, 23, 28, 30], "step_fn": [7, 12], "step_length": [13, 31], "step_siz": 31, "steps_list": 9, "stereo": 3, "sticki": [], "still": [0, 2, 3, 5, 6, 11, 13, 25, 29, 30, 31], "stimuli": 12, "stk": [27, 28], "stk2100": [27, 28], "stk3155": [15, 23, 24, 26], "stk4021": [27, 28], "stk4051": [27, 28], "stk4155": [24, 26], "stk5000": 27, "stochast": [0, 1, 5, 6, 8, 11, 12, 30], "stock": 4, "stoke": 12, "stone": [0, 7], "stop": [1, 4, 9, 13, 14, 18, 30], "storag": [5, 29, 30], "store": [0, 1, 2, 3, 6, 11, 13, 25, 28, 31], "storehaug": [26, 28], "str": [1, 3, 4], "straight": [0, 6, 8, 13, 28, 30], "straightforward": [0, 2, 3, 5, 6, 8, 9, 10, 13, 22, 28, 29, 30], "strategi": [0, 1, 9, 28], "stratifi": 6, "stream": 31, "strength": [0, 5, 14, 29, 30], "stretch": 11, "strict": [8, 13, 30], "strictli": [8, 13, 30], "stride": [4, 22], "strike": 6, "string": 1, "stroke": 7, "strong": [3, 6, 9, 10, 12, 22, 25, 31], "strongli": [0, 8, 15, 20, 21, 22], "stronli": [], "structur": [0, 1, 2, 3, 6, 9, 10, 12, 21, 28], "stuck": [1, 13, 30, 31], "student": [0, 15, 23, 24, 26, 27, 28], "studi": [0, 3, 4, 5, 6, 7, 8, 11, 12, 13, 21, 23, 27, 28, 29, 30, 31], "studier": 27, "style": [7, 9, 20, 22, 28], "stylesheet": [], "st\u00f8land": 26, "sub": [9, 12, 31], "subdivid": [0, 22, 28], "subfield": 0, "subgradi": 31, "subject": [6, 8, 25], "sublicens": [], "sublinear": 31, "submit": 28, "subplot": [0, 1, 3, 4, 6, 7, 8, 9, 10, 14, 28], "subplots_adjust": [8, 25], "subprogram": [22, 28], "subproject": [], "subract": [0, 29], "subroutin": [0, 28], "subscript": 1, "subsequ": [1, 4, 5, 6, 12, 22, 25, 29, 30], "subset": [1, 6, 9, 12, 13, 21, 28, 30, 31], "subspac": [0, 8, 11, 29], "substanti": [9, 10, 31], "substep": 11, "substitut": [3, 6, 12, 16, 22], "subsubset": 9, "subtask": 6, "subtl": 1, "subtract": [0, 4, 5, 6, 11, 13, 18, 19, 22, 23, 25, 29, 31], "subtre": 9, "succeed": [0, 4, 28], "success": [3, 7, 9, 13, 25], "successfulli": [4, 9], "succinctli": 31, "sudo": [0, 21, 23, 28], "suffer": [0, 1, 2, 5, 10, 28, 29, 30], "suffici": [1, 6, 8, 11, 13, 30], "suggest": [1, 13, 23, 27, 30, 31], "suit": [8, 12], "suitabl": [0, 15, 19, 25, 29, 31], "sum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 19, 22, 25, 28, 29, 30, 31], "sum_": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 19, 22, 23, 25, 28, 29, 30, 31], "sum_i": [0, 2, 5, 6, 8, 13, 19, 23, 29, 30, 31], "sum_j": [6, 18, 31], "sum_ja_": 0, "sum_k": [6, 8, 12, 22], "sum_logist": 13, "sum_m": 3, "sum_n": 3, "sum_nx_": 3, "summar": [5, 6, 9], "summari": [1, 3, 4, 10, 24, 30, 31], "summat": [0, 3, 16, 29, 30], "sunni": 9, "super": [5, 29, 30, 31], "superfici": 3, "superscript": [1, 12], "supervis": [0, 5, 6, 7, 9, 12, 21, 28, 29, 30], "supplement": [7, 23], "suppli": [], "support": [0, 1, 9, 10, 11, 13, 20, 21, 28, 29, 31], "suppos": [0, 5, 6, 7, 8, 10, 11, 12, 13, 22, 28, 29, 30, 31], "suppress": [5, 13, 30], "sure": [0, 1, 4, 6, 16, 20, 23], "surf": 6, "surfac": [0, 6, 28, 31], "surpass": 6, "surpris": [0, 28], "surround": [3, 21], "survei": [0, 5, 6, 28, 29], "svc": [8, 9, 10], "svd": [0, 6, 11, 28], "svdinv": 5, "svm": [8, 9, 10, 11], "svm_clf": [8, 10], "swath": [5, 29, 30], "switch": 0, "sy": [13, 30, 31], "symbol": [1, 5, 11, 13, 21, 25, 28, 29, 30], "symmeteri": 1, "symmetr": [0, 5, 8, 11, 12, 13, 22, 28, 29], "symmetri": 6, "sympi": [0, 21, 23, 28], "synonim": 25, "syntax": 13, "system": [0, 1, 3, 4, 6, 7, 9, 10, 12, 13, 15, 21, 22, 23, 28, 30, 31], "systemat": [4, 6], "t": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 26, 28, 30, 31], "t0": [3, 6, 13, 31], "t1": [2, 13, 31], "t2": 2, "t3": 2, "t_": 2, "t_0": [2, 9, 13, 31], "t_1": [13, 31], "t_b": 10, "t_i": [1, 2, 5, 12, 29, 30], "t_j": 12, "t_k": 9, "tabl": [9, 23, 25, 26, 28], "tabul": [0, 28], "tabular": 28, "tackl": 4, "tag": [2, 3, 4, 5, 6, 7, 12, 13, 14, 22, 25, 29, 30], "taht": [0, 28], "tail": 25, "tailor": [2, 8, 11, 28], "taiwan": [0, 28], "take": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 19, 21, 22, 25, 28, 29, 30, 31], "taken": [0, 1, 3, 6, 10, 13, 22], "tan": 3, "tangent": [1, 4, 12, 13, 30], "tanh": [1, 4, 7, 8, 12], "target": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 18, 19, 28, 29, 30, 31], "target_nam": 9, "task": [0, 1, 3, 6, 9, 11, 12, 14, 23, 28, 31], "tau": [3, 5, 25], "taught": 28, "tax": [], "taylor": [2, 13, 30], "taylornr": [13, 30], "tc": 8, "teach": [15, 24, 28], "team": 1, "teaser": 0, "technic": [0, 5, 6, 13, 23, 30, 31], "techniqu": [0, 1, 8, 10, 13, 21, 25, 27, 28, 29, 31], "technologi": [0, 1], "tell": [0, 4, 6, 10, 11, 13, 16, 25, 31], "temp": 1, "temp1": 1, "temp2": 1, "temperatur": [0, 9, 28], "templat": [18, 20], "temporarili": 1, "ten": [3, 28], "tend": [3, 5, 6, 8, 9, 10, 12, 13, 14, 29, 31], "tendenc": [0, 28], "tension": 6, "tensor": 3, "tensorflow": [0, 2, 4, 8, 14, 21, 22, 23, 27, 28, 29], "term": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 23, 25, 28, 29, 30, 31], "term1": [5, 6, 11], "term2": [5, 6, 11], "term3": [5, 6, 11], "term4": [5, 6, 11], "termin": [0, 4, 5, 9, 10, 13, 15, 29, 30, 31], "terminarl": 15, "terrain": 6, "terrain1": 6, "test": [3, 4, 5, 6, 7, 8, 9, 10, 13, 16, 20, 22, 23, 25, 28, 30, 31], "test_acc": 3, "test_accuraci": [1, 3], "test_error": 6, "test_imag": [3, 4], "test_ind": 6, "test_input": 4, "test_label": [3, 4], "test_loss": 3, "test_pr": 1, "test_predict": 1, "test_rnn": 4, "test_scor": [7, 10], "test_siz": [0, 1, 3, 5, 6, 10, 15, 17, 29, 30, 31], "test_split": 9, "testerror": [0, 6, 29], "testi": 4, "testpredict": 4, "testx": 4, "tex": [], "text": [0, 1, 2, 4, 5, 8, 9, 11, 13, 15, 18, 20, 22, 25, 27, 29, 30, 31], "textbf": [], "textbook": [16, 23, 29, 30], "textual": 9, "textur": 1, "tf": [1, 3, 4, 13, 14, 30], "th": [0, 1, 2, 5, 6, 7, 9, 12, 13, 14, 22, 23, 25, 28, 29, 31], "than": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 17, 21, 25, 28, 29, 31], "thank": [4, 6, 29, 31], "theano": [1, 21, 28], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 18, 20, 22, 23, 25, 28, 29, 30, 31], "them": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 13, 18, 19, 22, 23, 28, 29], "theme": [0, 15, 28], "themselv": [0, 23, 25, 28, 31], "thenc": 6, "theorem": [2, 6, 7, 29, 30], "theoret": [0, 4, 10], "theori": [0, 1, 3, 8, 9, 12, 13, 19, 21, 23, 27, 28, 31], "thereaft": [0, 5, 6, 11, 12, 22, 23, 28], "therebi": [0, 5, 7, 11, 23, 28, 29, 30], "therefor": [0, 1, 2, 3, 4, 6, 7, 8, 11, 13, 19, 25, 28, 29, 30, 31], "therein": 11, "thereof": [0, 6, 13, 28, 31], "theta": [0, 1, 4, 5, 6, 7, 13, 16, 23, 25, 28, 29, 30, 31], "theta1": 31, "theta2": 31, "theta_": [0, 1, 6, 7, 13, 28, 29, 30, 31], "theta_0": [0, 5, 6, 7, 16, 28, 29, 30, 31], "theta_0x_": [0, 28, 29], "theta_1": [0, 5, 6, 7, 28, 29, 30, 31], "theta_1x_": [0, 28, 29], "theta_1x_0": [0, 28], "theta_1x_1": [0, 7, 28], "theta_1x_2": [0, 28], "theta_1x_i": [7, 29, 30, 31], "theta_2": [0, 28, 29], "theta_2x_": [0, 28, 29], "theta_2x_0": [0, 28], "theta_2x_1": [0, 28], "theta_2x_2": [0, 7, 28], "theta_2x_i": 29, "theta_3x_i": 29, "theta_4x_i": 29, "theta_closed_form": 18, "theta_closed_formol": 18, "theta_closed_formridg": 18, "theta_gdol": 18, "theta_gdridg": 18, "theta_i": [0, 1, 5, 28, 29, 30], "theta_j": [0, 5, 6, 18, 28, 29, 31], "theta_k": [30, 31], "theta_linreg": [13, 30, 31], "theta_ol": 18, "theta_p": 7, "theta_px_p": 7, "theta_ridg": 18, "theta_t": [13, 31], "theta_tru": 18, "thetaith": 31, "thetavalu": 5, "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31], "thing": [0, 1, 2, 4, 5, 7, 9, 15, 16, 18, 25, 28], "think": [0, 1, 3, 4, 6, 9, 12, 13, 14, 25, 28, 29, 30, 31], "third": [0, 3, 6, 13, 26, 28, 30, 31], "thirti": 7, "thorughout": 28, "those": [0, 3, 5, 6, 8, 9, 10, 11, 22, 23, 28, 29, 30, 31], "though": [1, 2, 3, 4, 13, 16, 17, 19, 22, 25, 31], "thought": [6, 14, 23, 25], "thousand": [0, 1, 23, 29, 31], "three": [0, 1, 3, 5, 6, 8, 9, 12, 22, 23, 24, 25, 26, 28, 29, 30], "threshold": [1, 3, 9, 10, 11, 12, 13, 31], "through": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12, 13, 14, 15, 21, 22, 23, 25, 28, 29, 30, 31], "throughout": [0, 4, 5, 14, 15, 21, 22, 25, 28], "throw": [3, 6, 25], "thu": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 26, 28, 29, 30, 31], "thumb": [0, 6, 23, 29], "thursdai": [], "tibshirani": [6, 19, 23, 27, 28], "tick_param": 6, "ticker": [6, 13, 25, 30, 31], "tif": 6, "tight_layout": [1, 7], "tightli": 11, "tild": [0, 5, 6, 7, 11, 19, 23, 25, 28, 29, 30, 31], "till": [0, 4, 7, 8, 9, 10, 12, 22, 28, 29], "time": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 25, 28, 29, 30], "timeit": 4, "timer": 4, "tini": [1, 31], "tip": 3, "titl": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 15, 20, 25, 28, 30, 31], "tm": [], "tmp": 13, "tn": [2, 3, 7], "to_categor": [1, 3, 4], "to_categorical_numpi": 1, "to_numer": [0, 6, 28], "todai": 3, "togeth": [0, 3, 6, 8, 11, 13, 21, 28], "toi": 14, "token": [], "told": 13, "toler": [2, 14], "tolist": 4, "tomographi": 12, "too": [0, 2, 4, 5, 6, 9, 11, 13, 17, 18, 25, 27, 29, 30, 31], "took": [8, 28], "tool": [0, 1, 3, 6, 13, 15, 21, 29], "toolbox": 8, "top": [0, 3, 5, 6, 9, 10, 19, 21, 28], "topic": [0, 5, 6, 7, 8, 21, 23, 29, 30], "topolog": [3, 12], "topologi": [1, 12], "torkjellsdatt": [26, 28], "tort": [], "toss": [10, 25], "total": [0, 1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 13, 14, 22, 25, 26, 28, 29, 30, 31], "total_loss": 4, "totalclustervari": 14, "totalscatt": 14, "toward": [1, 2, 7, 12, 13, 15, 30], "towardsdatasci": 31, "town": [], "tp": [4, 7], "tpng": 9, "tpu": [13, 21, 28], "tqdm": 6, "tr": [], "track": [3, 13, 14, 15, 22, 29, 30, 31], "tract": [], "tractabl": [0, 28, 29], "trade": [5, 9, 20, 31], "tradeoff": [0, 5, 19, 23, 28, 29, 30], "tradit": [0, 1, 4, 6, 28], "train": [2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 16, 17, 20, 23, 30, 31], "train_accuraci": [0, 1, 3, 28], "train_dataset": 4, "train_end": [0, 1, 29], "train_error": 6, "train_imag": [3, 4], "train_ind": 6, "train_label": [3, 4], "train_pr": 1, "train_siz": [0, 1, 3, 29], "train_step": 4, "train_test_split": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "train_test_split_numpi": [0, 1, 29], "trainable_vari": 4, "trained_model": [6, 29, 31], "trainerror": [0, 29], "traini": 4, "training_checkpoint": 4, "training_dataset": 4, "training_gradi": [13, 31], "trainingerror": 6, "trainpredict": 4, "trainscor": 4, "trainx": 4, "trait": [0, 28], "trajectori": [4, 31], "transfer": [9, 28], "transform": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 21, 22, 28, 29, 30, 31], "transit": [6, 12], "translat": [1, 4, 6, 10, 28, 29, 31], "transpos": [1, 5, 11, 22, 29, 30], "travers": [0, 5], "treat": [0, 1, 3, 6, 12, 13, 18, 25, 28, 29, 30, 31], "tree": [0, 1, 21, 28], "tree_clf": [9, 10], "tree_clf_": 9, "tree_clf_sr": 9, "tree_reg": 9, "tree_reg1": 9, "tree_reg2": 9, "trend": 25, "treue": 7, "trevor": [19, 23, 27], "tri": [2, 3, 4, 9, 13, 16, 31], "triain": 0, "trial": [0, 2, 4, 6, 13, 25, 28, 30, 31], "triangl": [13, 30], "triangular": 22, "trick": [3, 4, 8, 11, 13, 25, 31], "trickier": 25, "tridiagon": 22, "trillion": 21, "trim": [], "trivial": [0, 1, 5, 11, 25, 28, 30], "troffa": [], "troubl": [0, 8, 12, 15, 29, 31], "truck": 3, "true": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "true_beta": 29, "true_fun": 6, "true_theta": [6, 31], "truli": 28, "try": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 18, 21, 22, 23, 25, 28, 29, 30, 31], "tr\u00f6ger": [], "tucker": 8, "tuesdai": [26, 28], "tumor": [7, 9], "tumour": 7, "tunabl": 1, "tune": [4, 9, 13, 22, 28, 31], "turn": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 25, 28, 29, 30, 31], "tutori": [1, 4], "tv": 2, "tveito": 2, "tweak": [1, 4, 10, 25], "twice": [13, 30], "twist": 11, "two": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 17, 22, 23, 24, 25, 27, 28, 29, 30, 31], "tx": [13, 30, 31], "tx_1": [13, 30], "txt": [4, 15, 20], "ty": [13, 30], "type": [0, 1, 3, 6, 8, 10, 13, 22, 25, 29, 30, 31], "typeset": 20, "typic": [0, 1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 20, 25, 28, 29, 30, 31], "typo": 23, "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 22, 23, 25, 27, 28, 29, 30, 31], "u_": 22, "u_i": 12, "u_m": 10, "ua": [0, 28], "ubuntu": [0, 21, 23, 28], "uci": 23, "uio": [15, 23, 26, 27], "un": 14, "unabl": 15, "unari": [22, 28], "unbalanc": [6, 9], "unbias": [0, 5, 6, 28], "uncent": [6, 29, 31], "uncertainti": [0, 5, 28], "uncertitud": 25, "unchang": [1, 3], "uncorrel": [10, 25], "undefin": [5, 29, 30], "under": [0, 1, 5, 6, 10, 13, 21, 23, 28, 29, 30, 31], "underdetermin": [0, 28], "underfit": [1, 6], "underflowproblem": 5, "undergo": 5, "undergradu": [24, 26], "underli": [0, 1, 9, 13, 18, 25, 28, 31], "underlin": [], "underscor": [], "underset": [4, 14], "understand": [0, 1, 3, 5, 6, 10, 13, 14, 15, 19, 20, 21, 28, 29, 30, 31], "understood": [8, 13], "undesir": 8, "undetermin": [5, 8], "undo": 4, "unexpect": 6, "unexpected": 25, "unexplain": 18, "unfair": [6, 29], "unfortun": [1, 8, 9, 10], "unicode_liter": [8, 9], "uniform": [0, 1, 5, 6, 11, 13, 23, 25, 28, 30, 31], "uniformli": [13, 25, 30, 31], "unifrompdf": 25, "unimport": [13, 30], "union": [5, 6], "uniqu": [0, 2, 6, 13, 14, 22, 28], "unique_cluster_label": 14, "unit": [0, 1, 3, 4, 5, 10, 12, 18, 25, 28, 29, 30, 31], "unitari": [5, 6, 22, 29, 30], "unitarili": [22, 28], "uniti": 25, "univari": 25, "univers": [0, 1, 2, 13, 21, 23, 24, 26, 28, 29, 30, 31], "unix": 1, "unknow": [0, 22, 28], "unknown": [0, 1, 3, 4, 5, 6, 8, 10, 13, 22, 23, 28, 29, 30, 31], "unknowwn": 12, "unlabel": 1, "unless": [0, 3, 6, 11, 13, 23, 28, 30], "unlik": [1, 3, 8, 13, 30, 31], "unnecessarili": 9, "unord": 3, "unpublish": 31, "unravel": 1, "unrol": [3, 11], "unscal": 19, "unseen": [0, 7, 9, 15], "unstabl": 1, "unsupervis": [0, 1, 4, 12, 21, 28], "unsymmetr": [22, 28], "until": [1, 2, 4, 9, 12, 13, 14, 30, 31], "untouch": 0, "unusu": 12, "up": [1, 3, 4, 5, 6, 8, 10, 11, 13, 14, 16, 18, 19, 20, 21, 22, 23, 25, 26, 31], "updat": [1, 2, 10, 12, 13, 14, 15, 18], "uploa": 28, "upload": [15, 20, 21, 23, 27], "upon": [0, 1, 6, 7, 11, 22], "upper": [0, 8, 9, 16, 22, 29], "uppercas": [22, 28], "upsampl": 4, "upscal": 4, "url": [28, 29], "us": [4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 17, 20, 22, 25, 27], "usag": [0, 8, 21, 28, 29], "usd": [], "usd10000": [], "use_bia": 4, "usecol": [0, 28], "useless": 1, "user": [0, 1, 2, 4, 6, 7, 15, 21, 22, 23, 28, 29], "usernam": [15, 23], "usetex": 25, "usg": 6, "usr": 25, "usual": [0, 3, 4, 7, 12, 13, 14, 28, 31], "ut": 5, "utf": [], "util": [1, 3, 4, 6, 7, 10, 14, 19, 28], "ux": 22, "v": [2, 4, 5, 6, 11, 13, 15, 21, 29, 30], "v0": 25, "v1": 25, "v2": 25, "v5": [], "v_": 31, "v_0": [11, 31], "v_t": 31, "va": 1, "vahid": 28, "val": 13, "val_accuraci": 3, "val_loss": 4, "vale": 2, "valid": [0, 1, 4, 7, 9, 10, 13, 21, 25, 28, 29, 31], "validation_data": 3, "validation_split": 4, "valu": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 20, 21, 22, 23, 28, 31], "valuat": 9, "valy": 4, "van": [0, 19, 23, 28, 29, 30, 31], "vandenbergh": [8, 13, 30], "vandermond": [0, 28], "vanilla": [0, 6, 11, 14, 29, 31], "vanish": [1, 4, 13, 25, 30], "var": [5, 6, 10, 11, 19, 23, 25, 29], "var_x": 25, "varabl": 8, "varepsilon": [5, 6, 19], "varepsilon_": [5, 6], "varepsilon_i": [5, 6], "vari": [0, 1, 3, 5, 6, 10, 28], "variabl": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 14, 22, 28, 29, 31], "varianc": [0, 1, 5, 7, 9, 10, 11, 13, 14, 18, 20, 21, 22, 25, 28, 29, 30, 31], "variance_i": [5, 11, 29], "variance_x": [5, 11, 29], "variant": [0, 1, 6, 8, 12, 13, 28, 29, 30, 31], "variat": [3, 4, 11, 28], "varieti": [0, 3, 12, 21, 23, 28], "variou": [1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "varydimens": 4, "vast": 31, "vastli": 3, "vaue": 1, "vault": 0, "vdot": [2, 13, 30, 31], "ve": [23, 31], "vec": 6, "vector": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 17, 18, 21, 30, 31], "vector_mean": 14, "ventur": [0, 8, 21, 28], "venv": 15, "verbos": [1, 3, 4], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 23, 25, 27, 28, 29, 30, 31], "verifi": [3, 11, 22, 28], "versatil": [8, 28], "versicolor": [8, 9], "version": [0, 3, 10, 13, 14, 15, 21, 22, 23, 25, 28], "versu": [1, 31], "vert": [0, 1, 5, 6, 7, 8, 9, 11, 13, 16, 17, 28, 29, 30, 31], "vert_1": [5, 6, 29, 30, 31], "vert_2": [5, 6, 11, 17, 29, 30, 31], "via": [0, 5, 6, 7, 8, 9, 10, 11, 12, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31], "vidal": 11, "video": [0, 1, 12, 21, 24, 26, 28, 29, 30], "view": [1, 3, 5, 6, 12, 13, 25, 27, 28, 30, 31], "violat": 8, "virginica": 9, "viridi": [0, 1, 2, 3, 28], "virtanen": [], "virtual": [1, 31], "viscos": 13, "viscou": 13, "visibl": 15, "vision": [0, 3], "visit": 31, "visual": [0, 3, 11, 12, 18, 21, 28, 29], "visualis": 1, "visualstudio": [15, 16, 19], "viz": [6, 8, 25], "vmap": 13, "vmax": [1, 6], "vmh0zpt0tli": 31, "vmin": [1, 6], "voic": 3, "volatil": 31, "volum": [0, 3, 28], "vote": [10, 28], "voting_clf": 10, "votingclassifi": 10, "votingsimpl": 10, "vscode": [], "vstack": [5, 11, 22, 25, 28, 29], "vt": [5, 29, 30], "w": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 22, 25, 28, 29, 30, 31], "w1": 8, "w2": [8, 11], "w3": 8, "w_": [1, 12], "w_1": [8, 22], "w_1x_": 8, "w_1x_1": 8, "w_2": [8, 22], "w_2x_": 8, "w_2x_2": 8, "w_3": 22, "w_4": 22, "w_hidden": 2, "w_i": [1, 2, 10], "w_ix_i": 12, "w_j": 22, "w_m": 22, "w_output": 2, "w_px_": 8, "w_px_p": 8, "w_t": [], "wa": [1, 3, 4, 5, 6, 7, 10, 11, 12, 14, 17, 22, 28, 29, 31], "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 19, 22, 25, 28, 29, 30, 31], "walk": 9, "walker": 25, "wall": 31, "walt": [], "wang": [0, 28], "want": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20, 21, 23, 25, 28, 29, 30, 31], "warn": 4, "warrant": 6, "warranti": [], "wast": [3, 31], "watch": [21, 30, 31], "wave": 3, "wavelet": 8, "wcag": [], "we": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 29, 30], "weak": [9, 10, 14], "weaker": 31, "weather": [1, 12], "web": [21, 24, 26, 28], "webpag": 28, "websit": [6, 22, 23, 24, 28], "wedg": [8, 25], "wednesdai": [26, 28], "wee": 11, "week": [0, 5, 6, 7, 20, 23, 24, 26], "weekli": [15, 16, 21, 23, 24, 26, 27, 28], "weight": [1, 2, 3, 6, 7, 9, 10, 12, 13, 18, 25, 31], "weigth": 2, "welcom": [8, 15, 21], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 20, 21, 22, 23, 25, 27, 28, 29, 30, 31], "went": 8, "were": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 25, 28, 31], "wessel": [0, 19, 23, 28, 29, 30, 31], "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 25, 31], "whatev": 3, "when": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 22, 23, 25, 28, 29, 30], "whenev": [13, 15, 25, 31], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31], "wherea": [6, 25, 31], "wherefrom": 23, "wherein": [1, 12], "whether": [0, 3, 5, 7, 9, 23, 25, 28], "which": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30], "whichev": [1, 3], "while": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 19, 20, 25, 28, 29, 30, 31], "white": 9, "whiteboad": 31, "whiteboard": [29, 30, 31], "who": [0, 15], "whole": [1, 3, 4, 5, 9, 11, 13, 31], "whom": [], "whose": [0, 6, 10, 25, 29], "whow": [11, 29], "why": [0, 1, 3, 6, 13, 15, 16, 17, 19, 23, 29, 30], "wide": [0, 1, 3, 6, 7, 12, 21, 22, 23, 28], "widehat": 6, "width": [0, 3, 8, 9, 28], "wieringen": [0, 19, 23, 28, 29, 30, 31], "wiki": 23, "wikipedia": 23, "win": [10, 31], "wind": 9, "window": [], "wing": [26, 28], "winther": 2, "wiothout": 6, "wiscons": 7, "wisconsin": 10, "wisdom": [6, 29, 31], "wise": [1, 5, 12, 13, 29, 30, 31], "wish": [0, 2, 5, 7, 8, 11, 13, 14, 18, 22, 23, 28, 29, 30, 31], "with_std": [0, 29], "wither": 6, "within": [0, 2, 3, 4, 7, 9, 12, 13, 14, 25, 27, 28, 30], "withinclust": 14, "without": [0, 1, 5, 6, 8, 9, 11, 12, 13, 15, 18, 23, 28, 29, 30, 31], "won": [0, 15, 28], "wonder": 8, "word": [0, 1, 3, 4, 5, 6, 7, 14, 25, 28, 29, 30, 31], "work": [0, 1, 4, 6, 7, 8, 9, 13, 15, 16, 18, 19, 20, 21, 23, 24, 25, 26, 28, 29, 31], "workabl": 31, "workaround": [], "workhors": 31, "workload": 31, "workshop": 28, "world": [0, 8, 16, 29], "worldwid": [0, 28], "worri": 15, "wors": [0, 1, 3, 4, 6, 28, 31], "worth": [9, 19], "worthi": 23, "would": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 18, 20, 22, 23, 25, 28, 29, 30, 31], "wrap": [6, 22, 28], "write": [0, 1, 2, 3, 5, 6, 7, 8, 12, 13, 15, 16, 18, 22, 28, 29, 31], "written": [0, 2, 3, 5, 11, 12, 13, 16, 21, 22, 23, 25, 28, 29, 30, 31], "wrong": [1, 8, 15], "wrongli": 10, "wrote": [5, 11, 29], "wrt": [10, 13, 31], "wth": [10, 13, 31], "www": [20, 21, 22, 23, 27, 28, 30, 31], "wx_1": 8, "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 28, 30, 31], "x0": 8, "x1": [4, 8, 9, 10, 13], "x1_exampl": 8, "x1d": 8, "x2": [8, 9, 10, 13], "x2d": [8, 11], "x2d_train": 11, "x2dsl": 11, "x3": 8, "x_": [0, 2, 3, 5, 6, 8, 10, 11, 13, 14, 22, 25, 28, 29, 30, 31], "x_0": [0, 5, 11, 18, 22, 28, 29], "x_1": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 18, 22, 25, 28, 29, 30, 31], "x_2": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 22, 25, 28, 29, 30], "x_3": [8, 22, 25], "x_4": 22, "x_6": 18, "x_center": 11, "x_data": 1, "x_data_ful": 1, "x_hidden": 2, "x_i": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 25, 28, 29, 30, 31], "x_input": 2, "x_ix_": [0, 28], "x_iy_i": 8, "x_j": [0, 2, 8, 9, 12, 16, 25, 29, 31], "x_jy_j": 8, "x_k": [12, 14, 22, 25, 29], "x_l": 25, "x_m": [6, 12, 22, 25], "x_mean": [18, 31], "x_n": [0, 2, 3, 6, 8, 11, 12, 13, 22, 25, 28, 30], "x_new": [9, 10], "x_norm": [18, 31], "x_offset": [6, 29, 31], "x_output": 2, "x_p": [3, 7, 9], "x_poli": 9, "x_poly10": 9, "x_pred": 4, "x_prev": 2, "x_reduc": 11, "x_sampl": 19, "x_scale": 8, "x_small": 13, "x_std": [18, 31], "x_t": 31, "x_test": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 29, 30, 31], "x_test_": 17, "x_test_own": 6, "x_test_scal": [0, 6, 7, 9, 10, 11, 29, 31], "x_tot": 4, "x_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "x_train_": 17, "x_train_mean": [6, 29, 31], "x_train_own": 6, "x_train_scal": [0, 6, 7, 9, 10, 11, 29, 31], "x_val": 1, "xarrai": [21, 28], "xavier": 1, "xbnew": [13, 30, 31], "xcode": [0, 21, 23, 28], "xdclassiffierconfus": 10, "xdclassiffierroc": 10, "xg_clf": 10, "xgb": 10, "xgbclassifi": 10, "xgboost": 9, "xgboot": 10, "xgbregressor": 10, "xgparam": 10, "xgtree": 10, "xi": [8, 13, 31], "xi_": 8, "xi_1": 8, "xi_i": 8, "xk": 8, "xla": [13, 21, 28], "xlabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 25, 28, 29, 30, 31], "xlim": [6, 10], "xm": 9, "xmesh": 13, "xnew": [0, 13, 28, 30, 31], "xp": 25, "xpanda": [0, 29], "xpd": [5, 11, 29], "xplot": 0, "xscale": [0, 29], "xsr": 9, "xt_x": [13, 30, 31], "xtest": 6, "xtick": [3, 6, 8, 9], "xtrain": 6, "xu": [0, 28], "xx": [0, 22, 28], "xy": [0, 6, 8, 22, 28], "xytext": 8, "xyz": [], "xz": [22, 28], "y": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "y1": 4, "y2": 4, "y3": 4, "y_": [0, 1, 5, 6, 10, 11, 22, 28, 29], "y_0": [0, 5, 11, 22, 28, 29], "y_1": [0, 5, 8, 9, 11, 13, 22, 28, 29, 30, 31], "y_1y_1": 8, "y_1y_1k": 8, "y_1y_2": 8, "y_1y_2k": 8, "y_1y_n": 8, "y_1y_nk": 8, "y_2": [0, 5, 8, 9, 11, 22, 28, 29], "y_2y_1": 8, "y_2y_1k": 8, "y_2y_2": 8, "y_2y_2k": 8, "y_3": [0, 9, 22], "y_4": 22, "y_center": [18, 31], "y_data": [0, 1, 5, 6, 28, 29, 30, 31], "y_data_ful": 1, "y_decis": 8, "y_fit": [0, 29], "y_i": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19, 22, 23, 28, 29, 30, 31], "y_if_": 10, "y_ix_": [0, 28], "y_ix_i": [7, 8, 13, 29, 30, 31], "y_iy_jk": 8, "y_j": [6, 8, 12, 23], "y_k": 12, "y_m": 22, "y_mean": [18, 31], "y_model": [0, 4, 5, 6, 28, 29, 30, 31], "y_n": [8, 13, 30, 31], "y_ny_1": 8, "y_ny_1k": 8, "y_ny_2": 8, "y_ny_2k": 8, "y_ny_n": 8, "y_ny_nk": 8, "y_offset": [6, 17, 29, 31], "y_plot": 9, "y_pred": [0, 1, 4, 6, 7, 8, 9, 10, 29, 31], "y_pred1": 9, "y_pred2": 9, "y_pred_rf": 10, "y_pred_tre": 10, "y_proba": [7, 10], "y_sampl": 19, "y_scaler": [6, 29, 31], "y_test": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 29, 30, 31], "y_test_onehot": 1, "y_test_predict": [], "y_tot": 4, "y_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "y_train_mean": [6, 29, 31], "y_train_onehot": 1, "y_train_predict": [], "y_train_scal": [6, 29, 31], "y_val": 1, "ye": [3, 6, 7], "year": [0, 21, 28], "yet": [0, 1, 6, 8, 11, 13, 20, 28], "yi": [13, 31], "yield": [0, 2, 5, 6, 8, 10, 12, 13, 14, 22, 25, 28, 30, 31], "yk": 8, "ylabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 25, 28, 29, 30, 31], "ylim": [3, 6], "ym": 9, "ymesh": 13, "yn": 0, "yo": [8, 9, 10], "yoshiki": [], "yoshua": [1, 27], "you": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31], "young": 0, "your": [1, 2, 4, 5, 6, 8, 11, 13, 15, 17, 19, 20, 21, 22, 28, 30, 31], "your_model_object": 16, "yourself": [11, 13, 28, 30], "youtu": [29, 30], "youtub": [21, 30, 31], "ypred": 6, "ypredict": [0, 13, 28, 29, 30, 31], "ypredict2": [13, 30, 31], "ypredictlasso": [5, 30], "ypredictol": [0, 5, 30], "ypredictown": [6, 29, 31], "ypredictownridg": [6, 29, 30, 31], "ypredictridg": [0, 5, 6, 29, 30, 31], "ypredictskl": [6, 29, 31], "ytest": 6, "ytick": [3, 6, 8, 9], "ytild": [0, 6, 28, 29], "ytildelasso": [5, 30], "ytildenp": [0, 28, 29], "ytildeol": [0, 5, 30], "ytildeownridg": [6, 29, 30, 31], "ytilderidg": [5, 6, 29, 30, 31], "ytrain": 6, "yuxi": 28, "yx": [22, 28], "yy": [22, 28], "yz": [22, 28], "z": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 22, 25, 28, 29], "z_": [1, 2, 12, 22, 28], "z_0": [22, 28], "z_1": [22, 28], "z_2": [22, 28], "z_c": 1, "z_h": 1, "z_hidden": 2, "z_i": [1, 12], "z_j": [1, 12], "z_k": [12, 29], "z_m": 1, "z_mod": 9, "z_o": 1, "z_output": 2, "za": [], "zaman": 25, "zaxi": 6, "zero": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "zeros_lik": 4, "zeroth": 29, "zfill": 4, "zip": [4, 6], "zm_h": [0, 28], "zn": [], "zone": [], "zoom": 28, "zscout": [], "zx": [22, 28], "zy": [22, 28], "zz": [22, 28], "\u00f8yvind": [6, 29, 31]}, "titles": ["3. Linear Regression", "14. Building a Feed Forward Neural Network", "15. Solving Differential Equations with Deep Learning", "16. Convolutional Neural Networks", "17. Recurrent neural networks: Overarching view", "4. Ridge and Lasso Regression", "5. Resampling Methods", "6. Logistic Regression", "8. Support Vector Machines, overarching aims", "9. Decision trees, overarching aims", "10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods", "11. Basic ideas of the Principal Component Analysis (PCA)", "13. Neural networks", "7. Optimization, the central part of any Machine Learning algortithm", "12. Clustering and Unsupervised Learning", "Exercises week 34", "Exercises week 35", "Exercises week 36", "Exercises week 37", "Exercises week 38", "Weekly Exercises 6", "Applied Data Analysis and Machine Learning", "2. Linear Algebra, Handling of Arrays and more Python Features", "Project 1 on Machine Learning, deadline October 6 (midnight), 2025", "Course setting", "1. Elements of Probability Theory and Statistical Data Analysis", "Teachers and Grading", "Textbooks", "Week 34: Introduction to the course, Logistics and Practicalities", "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression", "Week 36: Linear Regression and Gradient descent", "Week 37: Gradient descent methods"], "titleterms": {"": [8, 10, 30, 31], "0": [], "04": [], "05": [], "06": [], "07": [], "1": [0, 15, 16, 17, 18, 19, 20, 23, 29], "11": [], "15": 19, "19": 19, "1a": 18, "2": [0, 15, 16, 17, 18, 19, 20, 28, 29, 30], "20": [], "2017": [], "2018": [], "2019": [], "2023": 26, "2025": 23, "27": [], "2a": [], "2b": [], "3": [0, 15, 16, 17, 18, 19, 20, 29], "34": [15, 28], "35": [16, 29], "36": [17, 30], "37": [18, 31], "38": 19, "3a": 18, "3b": 18, "4": [0, 15, 16, 17, 18, 19, 20, 29], "4a": 18, "4b": 18, "5": [0, 16, 18, 19, 20], "6": [20, 23], "8": 31, "A": [0, 1, 4, 8, 9, 28], "And": [28, 29, 31], "But": 31, "In": 26, "Ising": 6, "The": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 15, 21, 28, 29, 30, 31], "To": 28, "With": [4, 30], "a11i": [], "about": [28, 29, 30], "abov": 30, "abstract": 20, "accuraci": 31, "across": 31, "activ": [1, 12], "ad": [0, 6, 20, 23, 28, 29], "adaboost": 10, "adagrad": [13, 31], "adam": [13, 31], "adapt": [10, 31], "add": [], "adjust": 1, "advanc": 23, "adversari": 4, "again": [3, 9], "ai": [23, 28], "aim": [8, 9, 28], "aka": 28, "al": 31, "algebra": [22, 28], "algorithm": [9, 10, 11, 12, 28, 29, 30, 31], "algortithm": [13, 30], "all": 8, "an": [0, 4, 10, 15, 20, 28], "analys": [5, 29, 30], "analysi": [0, 5, 6, 11, 21, 23, 25, 28, 29, 30], "analyt": [0, 16, 18], "ani": [13, 30], "anoth": [9, 30], "api": [], "appli": 21, "approach": [0, 8, 14, 28, 31], "approxim": 12, "architectur": 1, "arrai": [22, 28], "assist": 26, "august": [], "author": [], "autocorrel": 25, "autograd": [2, 13, 31], "automat": [13, 31], "avali": 20, "averag": 31, "b": 23, "back": [1, 11, 12, 29, 30], "background": [21, 23], "bag": 10, "base": [13, 31], "basic": [0, 5, 7, 9, 10, 11, 22, 29, 30], "batch": [1, 31], "bay": 5, "befor": 11, "better": 8, "bia": [6, 19, 23, 31], "binari": 1, "bind": 28, "bird": 10, "blind": [], "block": [], "boldsymbol": [18, 29], "book": 19, "boost": 10, "bootstrap": [6, 10], "boston": [], "breast": 1, "brief": 28, "bring": 12, "browser": [], "build": [1, 3, 9], "c": [23, 28], "calcul": [18, 29, 30], "can": [28, 31], "cancer": [1, 7, 9, 11], "cart": 9, "case": [8, 10, 25, 29, 30, 31], "cdn": [], "cell": [], "central": [13, 21, 25, 30], "chain": 12, "challeng": 31, "chang": 10, "changelog": [], "channel": 28, "chi": [0, 28], "choic": 17, "choos": [1, 31], "cifar01": 3, "citat": [], "classic": 11, "classif": [1, 9, 10], "classifi": 8, "clip": 1, "cluster": 14, "cnn": 3, "code": [1, 2, 5, 9, 11, 12, 13, 14, 15, 16, 20, 23, 28, 29, 30, 31], "collect": [1, 3], "color": [], "colorblind": [], "combin": 31, "commun": 28, "compar": [2, 10, 16], "comparison": [30, 31], "compet": 31, "compil": [], "complet": 29, "complex": [0, 6, 23, 29], "complic": 6, "compon": 11, "comput": [9, 19, 31], "computerlab": 28, "con": [9, 31], "concept": 25, "condit": 30, "conjug": 13, "constraint": 31, "contain": [], "content": [], "contn": 28, "contrast": [], "contributor": [], "converg": 31, "convex": [8, 13, 30, 31], "convolut": [3, 12], "copyright": [], "correct": 31, "correl": [11, 29], "correspond": [], "cost": [1, 10, 29, 30, 31], "cours": [21, 24, 27, 28], "covari": [5, 11, 25, 29], "cover": 28, "creat": [16, 20], "creator": [], "cross": [6, 23], "cython": 28, "d": 23, "dark": [], "data": [0, 1, 3, 6, 7, 9, 11, 15, 17, 18, 21, 25, 28, 29], "dataset": [1, 3, 18], "david": 28, "deadlin": [23, 28], "deadllin": 26, "decai": [2, 31], "decis": [9, 10], "decomposit": [5, 11, 22, 29, 30], "deeep": [], "deep": [1, 2, 28, 31], "defin": [1, 28], "definit": 19, "deflist": [], "degre": [0, 17, 29], "deliver": [15, 16, 19, 20], "deliveri": 23, "dens": 0, "depend": [], "deriv": [5, 12, 16, 17, 19, 29, 30, 31], "descent": [2, 10, 13, 18, 23, 30, 31], "design": 29, "detail": [3, 28], "develop": 1, "diagon": 11, "differ": [8, 31], "differenti": [2, 13, 31], "diffus": 2, "dimens": 31, "dimension": [2, 3, 8, 18], "direct": [], "disadvantag": 9, "discret": 25, "discrimin": 28, "distribut": [5, 25], "do": [1, 31], "document": 20, "doe": [29, 30], "domain": 25, "down": 1, "dropout": 1, "e": 23, "economi": [29, 30], "electron": 23, "element": [0, 25, 28], "elimin": 22, "empir": 31, "energi": 28, "ensembl": 10, "entropi": 9, "environ": [0, 15], "equat": [0, 2, 12, 29, 30], "error": [0, 10, 28, 29, 30], "essenti": 28, "et": 31, "etc": 28, "euler": 2, "evalu": 1, "evid": 31, "exampl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 28, 29, 30, 31], "exercis": [0, 6, 15, 16, 17, 18, 19, 20, 29], "expect": [19, 25], "experi": 25, "explor": 0, "exponenti": [2, 31], "express": [16, 17, 19, 29], "extend": 30, "extrapol": 4, "extrem": [10, 28], "ey": 10, "f": 23, "fall": 26, "famili": [1, 28], "famou": 22, "fantast": [29, 30], "faq": [], "featur": [9, 16, 22, 29], "februari": [], "feed": [1, 12], "figur": 20, "file": [], "final": [12, 29, 31], "find": [16, 18], "fine": 1, "first": [4, 12, 28, 30], "fit": [0, 10, 15, 16, 28, 30], "fix": [29, 30, 31], "forc": 3, "forest": 10, "form": 18, "format": [23, 28], "formula": 18, "forward": [1, 2, 12], "foster": 28, "fourier": 3, "frank": 6, "freedom": [0, 17, 29], "frequent": [29, 31], "frequentist": [0, 28], "from": [5, 10, 12, 28, 29, 30, 31], "full": [2, 31], "function": [0, 1, 6, 7, 8, 10, 11, 12, 13, 23, 25, 28, 29, 30, 31], "further": [3, 5, 29, 30], "g": 23, "gan": 4, "gaussian": 22, "gd": [13, 31], "gener": [4, 9, 28], "geometr": [11, 30], "get": 20, "gini": 9, "github": 15, "goal": [15, 16, 17, 18, 19, 20], "good": [0, 20, 28], "goodfellow": 31, "gotthard": [], "grade": [26, 28], "gradient": [1, 2, 10, 13, 18, 23, 30, 31], "greativ": [], "growth": 2, "h": 23, "ha": 21, "handl": [22, 28], "hessian": [29, 30, 31], "hidden": 2, "high": [], "hous": [], "how": 16, "hyperparamet": [1, 17], "hyperplan": 8, "i": [0, 1, 28], "id3": 9, "idea": 11, "ideal": 30, "ii": 28, "illustr": 30, "implement": [1, 16, 17, 18], "implic": [5, 29, 30], "import": [5, 22, 28, 29, 30], "improv": [1, 31], "includ": [13, 23, 31], "incorpor": [], "increment": 11, "index": 9, "inform": 26, "input": 2, "instal": [21, 23, 28], "instructor": 26, "interpret": [5, 11, 19, 28, 29, 30], "introduc": [11, 13, 29], "introduct": [0, 6, 20, 21, 22, 23, 28], "invers": [5, 22], "invert": [29, 30], "ipython": [], "iter": 10, "its": 29, "j": [], "jacobian": 29, "januari": [], "jax": 13, "julia": 28, "jungl": 10, "jupyt": [], "kera": [1, 3], "kernel": [8, 11], "lab": [30, 31], "lagrangian": 8, "lasso": [5, 6, 23, 29, 30], "last": [29, 31], "later": [5, 29, 30], "layer": [1, 2, 3, 12], "learn": [0, 1, 2, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 23, 28, 29, 30, 31], "least": [5, 6, 16, 19, 23, 28, 29, 30, 31], "lectur": [28, 30, 31], "level": 10, "librari": [21, 28], "licens": [], "light": [], "likelihood": 7, "limit": [1, 13, 25, 30, 31], "linear": [0, 8, 13, 15, 22, 28, 29, 30], "link": [5, 11, 27, 29], "literatur": 23, "logist": [7, 28], "loss": [29, 30, 31], "lu": 22, "machin": [0, 8, 13, 21, 23, 28, 30], "main": [25, 28], "make": [0, 9, 10, 20, 29], "mani": [10, 12], "markdown": [], "mass": 28, "materi": [23, 28, 29, 30, 31], "math": [5, 29, 30], "mathemat": [3, 5, 8, 29, 30], "matric": [5, 22, 28], "matrix": [1, 5, 11, 12, 16, 22, 28, 29, 30, 31], "matter": 0, "max": 29, "me": [], "mean": [0, 29, 30], "meet": [5, 10, 25, 28, 29], "memori": 31, "mercer": 8, "metadata": [], "method": [6, 9, 10, 13, 23, 28, 30, 31], "metric": 19, "midnight": 23, "min": 29, "mini": 31, "minibatch": 31, "minim": 28, "mit": [], "ml": 28, "mlp": 12, "mnist": [3, 4], "model": [0, 1, 4, 6, 12, 15, 17, 28], "moment": 31, "momentum": [13, 23, 31], "mondai": [30, 31], "moon": [8, 9], "more": [3, 6, 22, 23, 28, 29, 30, 31], "motiv": 31, "move": 31, "multilay": 12, "multipl": [1, 3, 17], "multipli": 8, "myst": [], "need": [23, 28], "network": [1, 2, 3, 4, 7, 12, 28, 31], "neural": [1, 2, 3, 4, 7, 12, 28, 31], "new": [4, 18], "newton": [30, 31], "node": [], "non": [8, 31], "none": 31, "normal": [0, 1], "notat": 12, "note": [23, 29, 30], "notebook": [], "novemb": [], "now": [1, 9, 13, 30, 31], "nuclear": [0, 28], "numba": 28, "number": [0, 2, 25, 29, 31], "numer": [2, 23, 25], "numpi": [22, 28], "object": 3, "obtain": 11, "octob": 23, "od": 2, "off": [6, 19, 23], "ol": [5, 6, 15, 16, 18, 23, 30], "one": [2, 12, 18, 30], "oper": 22, "optim": [1, 8, 13, 18, 21, 28, 29, 30, 31], "order": [13, 18, 31], "ordinari": [5, 6, 16, 19, 23, 28, 29, 30, 31], "organ": [0, 28], "oslo": 27, "other": [4, 9, 11, 12, 22, 23, 28], "our": [0, 4, 5, 11, 13, 23, 28, 29, 30], "outcom": [21, 28], "output": 2, "overarch": [0, 4, 8, 9, 28, 29], "overview": [10, 28, 31], "own": [0, 10, 11, 23, 28, 29], "packag": [22, 28], "panda": [28, 29], "paramet": [28, 29], "paramt": 18, "part": [13, 21, 23, 30], "partial": 2, "pass": 1, "pca": 11, "pdf": 25, "perceptron": 12, "perform": [1, 9], "period": 3, "perspect": 1, "pitaya": [], "plan": [29, 30, 31], "plethora": 28, "point": 4, "poisson": 2, "polici": [], "polynomi": [3, 16, 18, 30], "popul": 2, "popular": 28, "practic": [13, 26, 28, 31], "pre": [1, 3], "preambl": 23, "predict": 4, "preprocess": [29, 31], "prerequisit": [3, 21, 28], "present": 20, "princip": 11, "principl": 3, "pro": [9, 31], "probabl": [5, 25], "problem": [1, 2, 13, 28, 29, 30, 31], "procedur": [9, 28], "process": [1, 3], "program": [2, 13, 23, 30, 31], "project": [6, 20, 23, 26, 28], "prop": 13, "propag": [1, 12], "properti": [5, 25, 29, 30, 31], "python": [0, 9, 15, 21, 22, 28], "quick": 8, "quickli": [], "r": 28, "random": [10, 11, 25], "raphson": 30, "rate": [23, 31], "read": [9, 28, 29, 31], "real": [6, 28], "recommend": [28, 29], "recurr": [4, 12], "reduc": [0, 29], "reduct": 3, "refer": 23, "referenc": 20, "reformul": 2, "regress": [0, 5, 6, 7, 9, 10, 13, 15, 17, 18, 19, 23, 28, 29, 30, 31], "regular": 1, "relat": [], "relev": [27, 29], "relu": 1, "remark": 3, "remind": [6, 8, 28, 29, 30, 31], "replac": [13, 31], "report": [20, 23], "repositori": 15, "requir": [2, 21], "resampl": [6, 19, 23], "rescal": [6, 29], "residu": [29, 30], "resourc": 2, "result": [29, 30], "revisit": [13, 30, 31], "rewrit": [28, 29], "ridg": [0, 5, 6, 17, 18, 19, 23, 29, 30, 31], "rm": 13, "rmsprop": 31, "role": [], "rule": [12, 31], "rung": 23, "same": [13, 31], "sampl": 11, "scalabl": 31, "scale": [17, 18, 19, 29, 31], "schedul": 28, "schemat": 9, "scheme": 2, "scienc": 28, "scikit": [0, 1, 11, 28, 29, 30, 31], "second": [13, 18, 31], "semest": 26, "sensit": 30, "septemb": [19, 30, 31], "session": [30, 31], "set": [0, 2, 3, 9, 12, 15, 24, 28, 29, 30], "setup": 15, "sgd": [13, 31], "should": 1, "show": [], "similar": [13, 31], "simpl": [0, 4, 9, 13, 18, 28, 29, 30, 31], "simplest": 18, "singl": 10, "singular": [5, 11, 29, 30], "size": [29, 30, 31], "sklearn": 16, "slightli": 31, "smoothi": [], "sneak": 31, "soft": 8, "softmax": 1, "softwar": [23, 28], "solv": [2, 30], "solver": 13, "some": [13, 22, 29, 30], "sourc": [], "specifi": 2, "speed": 31, "sphinx": [], "split": [0, 15, 29], "squar": [0, 5, 6, 10, 16, 19, 23, 28, 29, 30, 31], "standard": [13, 29], "start": 20, "state": 0, "statist": [5, 6, 21, 25, 28], "steepest": [10, 13, 30], "step": 31, "stochast": [13, 23, 25, 31], "stop": 31, "strongli": [28, 31], "structur": [], "suggest": 28, "summari": [26, 28], "superposit": 3, "supervis": 1, "support": 8, "svd": [5, 29, 30], "synthet": 18, "systemat": 3, "t": 29, "take": 16, "taken": [28, 31], "teach": 26, "teacher": [26, 28], "team": [], "technic": 29, "techniqu": [6, 11, 23], "technologi": 21, "tensorflow": [1, 3], "tent": [26, 28], "term": [], "test": [0, 1, 15, 17, 29], "texmath": [], "text": 28, "textbook": [27, 28], "than": 30, "theorem": [5, 8, 11, 12, 25], "theoret": 31, "theori": 25, "theta": 18, "thi": 28, "time": 31, "tip": [13, 31], "todo": [], "togeth": 12, "tool": [23, 28], "top": 1, "topic": 28, "toward": 11, "trade": [6, 19, 23], "tradeoff": 6, "train": [0, 1, 4, 15, 28, 29], "transform": 3, "translat": [], "tree": [9, 10], "tuesdai": 30, "tune": 1, "two": [3, 8, 21], "type": [2, 4, 12, 28], "uio": 28, "univers": [12, 27], "unsupervis": 14, "up": [0, 2, 9, 12, 15, 28, 29, 30], "updat": [23, 31], "us": [0, 1, 2, 3, 7, 13, 16, 18, 19, 21, 23, 28, 29, 30, 31], "usag": 31, "v": [3, 31], "valid": [6, 23], "valu": [5, 11, 19, 25, 29, 30], "vari": 31, "variabl": [25, 30], "varianc": [6, 19, 23], "variou": 0, "vector": [8, 12, 16, 22, 28, 29], "versu": 28, "video": 31, "view": [0, 4, 10, 29], "virtual": 15, "visual": [1, 9], "wai": [9, 23], "wave": 2, "we": [28, 31], "wednesdai": 30, "week": [15, 16, 17, 18, 19, 28, 29, 30, 31], "weekli": 20, "welcom": [], "what": [0, 28, 29, 30], "when": 31, "which": [1, 31], "why": [28, 31], "wisconsin": 7, "workflow": [], "write": [4, 11, 20, 23, 30], "x": 29, "xgboost": 10, "yaml": [], "yet": 30, "your": [0, 10, 16, 18, 23, 29]}}) \ No newline at end of file +Search.setIndex({"alltitles": {"1a)": [[18, "a"]], "3a)": [[18, "id1"]], "3b)": [[18, "b"]], "4a)": [[18, "id2"]], "4b)": [[18, "id3"]], "A Classification Tree": [[9, "a-classification-tree"]], "A Frequentist approach to data analysis": [[0, "a-frequentist-approach-to-data-analysis"], [28, "a-frequentist-approach-to-data-analysis"]], "A better approach": [[8, "a-better-approach"]], "A first summary": [[28, "a-first-summary"]], "A quick Reminder on Lagrangian Multipliers": [[8, "a-quick-reminder-on-lagrangian-multipliers"]], "A simple example": [[4, "a-simple-example"]], "A soft classifier": [[8, "a-soft-classifier"]], "A top-down perspective on Neural networks": [[1, "a-top-down-perspective-on-neural-networks"]], "ADAM algorithm, taken from Goodfellow et al": [[31, "adam-algorithm-taken-from-goodfellow-et-al"]], "ADAM optimizer": [[13, "adam-optimizer"], [31, "id2"]], "Accuracy": [[31, "accuracy"]], "Activation functions": [[12, "activation-functions"]], "AdaGrad Properties": [[31, "adagrad-properties"]], "AdaGrad Update Rule Derivation": [[31, "adagrad-update-rule-derivation"]], "AdaGrad algorithm, taken from Goodfellow et al": [[31, "adagrad-algorithm-taken-from-goodfellow-et-al"]], "Adam Optimizer": [[31, "adam-optimizer"]], "Adam vs. AdaGrad and RMSProp": [[31, "adam-vs-adagrad-and-rmsprop"]], "Adam: Bias Correction": [[31, "adam-bias-correction"]], "Adam: Exponential Moving Averages (Moments)": [[31, "adam-exponential-moving-averages-moments"]], "Adam: Update Rule Derivation": [[31, "adam-update-rule-derivation"]], "Adaptive boosting: AdaBoost, Basic Algorithm": [[10, "adaptive-boosting-adaboost-basic-algorithm"]], "Adaptivity Across Dimensions": [[31, "adaptivity-across-dimensions"]], "Adding error analysis and training set up": [[28, "adding-error-analysis-and-training-set-up"], [29, "adding-error-analysis-and-training-set-up"]], "Adjust hyperparameters": [[1, "adjust-hyperparameters"]], "Algorithms and codes for Adagrad, RMSprop and Adam": [[31, "algorithms-and-codes-for-adagrad-rmsprop-and-adam"]], "Algorithms for Setting up Decision Trees": [[9, "algorithms-for-setting-up-decision-trees"]], "An Overview of Ensemble Methods": [[10, "an-overview-of-ensemble-methods"]], "An extrapolation example": [[4, "an-extrapolation-example"]], "An optimization/minimization problem": [[28, "an-optimization-minimization-problem"]], "And finally \\boldsymbol{X}\\boldsymbol{X}^T": [[29, "and-finally-boldsymbol-x-boldsymbol-x-t"]], "And finally ADAM": [[31, "and-finally-adam"]], "And what about using neural networks?": [[28, "and-what-about-using-neural-networks"]], "Another Example, now with a polynomial fit": [[30, "another-example-now-with-a-polynomial-fit"]], "Another example, the moons again": [[9, "another-example-the-moons-again"]], "Applied Data Analysis and Machine Learning": [[21, null]], "Autocorrelation function": [[25, "autocorrelation-function"]], "Automatic differentiation": [[13, "automatic-differentiation"]], "Back to Ridge and LASSO Regression": [[29, "back-to-ridge-and-lasso-regression"], [30, "back-to-ridge-and-lasso-regression"]], "Back to the Cancer Data": [[11, "back-to-the-cancer-data"]], "Background literature": [[23, "background-literature"]], "Bagging": [[10, "bagging"]], "Bagging Examples": [[10, "bagging-examples"]], "Basic Matrix Features": [[22, "basic-matrix-features"]], "Basic ideas of the Principal Component Analysis (PCA)": [[11, null]], "Basic math of the SVD": [[5, "basic-math-of-the-svd"], [29, "basic-math-of-the-svd"], [30, "basic-math-of-the-svd"]], "Basics": [[7, "basics"]], "Basics of a tree": [[9, "basics-of-a-tree"]], "Batch Normalization": [[1, "batch-normalization"]], "Batches and mini-batches": [[31, "batches-and-mini-batches"]], "Bayes\u2019 Theorem and Ridge and Lasso Regression": [[5, "bayes-theorem-and-ridge-and-lasso-regression"]], "Boosting, a Bird\u2019s Eye View": [[10, "boosting-a-bird-s-eye-view"]], "Bootstrap": [[6, "bootstrap"]], "Bringing it together, first back propagation equation": [[12, "bringing-it-together-first-back-propagation-equation"]], "Building a Feed Forward Neural Network": [[1, null]], "Building a tree, regression": [[9, "building-a-tree-regression"]], "Building neural networks in Tensorflow and Keras": [[1, "building-neural-networks-in-tensorflow-and-keras"]], "But none of these can compete with Newton\u2019s method": [[31, "but-none-of-these-can-compete-with-newton-s-method"]], "CNNs in more detail, building convolutional neural networks in Tensorflow and Keras": [[3, "cnns-in-more-detail-building-convolutional-neural-networks-in-tensorflow-and-keras"]], "Cancer Data again now with Decision Trees and other Methods": [[9, "cancer-data-again-now-with-decision-trees-and-other-methods"]], "Challenge: Choosing a Fixed Learning Rate": [[31, "challenge-choosing-a-fixed-learning-rate"]], "Choose cost function and optimizer": [[1, "choose-cost-function-and-optimizer"]], "Classical PCA Theorem": [[11, "classical-pca-theorem"]], "Clustering and Unsupervised Learning": [[14, null]], "Code for SVD and Inversion of Matrices": [[5, "code-for-svd-and-inversion-of-matrices"]], "Code with a Number of Minibatches which varies": [[31, "code-with-a-number-of-minibatches-which-varies"]], "Codes and Approaches": [[14, "codes-and-approaches"]], "Codes for the SVD": [[5, "codes-for-the-svd"], [29, "codes-for-the-svd"], [30, "codes-for-the-svd"]], "Coding Setup and Linear Regression": [[15, "coding-setup-and-linear-regression"]], "Collect and pre-process data": [[1, "collect-and-pre-process-data"]], "Communication channels": [[28, "communication-channels"]], "Compare Bagging on Trees with Random Forests": [[10, "compare-bagging-on-trees-with-random-forests"]], "Comparing with a numerical scheme": [[2, "comparing-with-a-numerical-scheme"]], "Comparison with OLS": [[30, "comparison-with-ols"]], "Computation of gradients": [[31, "computation-of-gradients"]], "Computing the Gini index": [[9, "computing-the-gini-index"]], "Conditions on convex functions": [[30, "conditions-on-convex-functions"]], "Conjugate gradient method": [[13, "conjugate-gradient-method"]], "Convergence rates": [[31, "convergence-rates"]], "Convex function": [[30, "convex-function"]], "Convex functions": [[13, "convex-functions"], [30, "convex-functions"]], "Convolution Examples: Polynomial multiplication": [[3, "convolution-examples-polynomial-multiplication"]], "Convolution Examples: Principle of Superposition and Periodic Forces (Fourier Transforms)": [[3, "convolution-examples-principle-of-superposition-and-periodic-forces-fourier-transforms"]], "Convolutional Neural Network": [[12, "convolutional-neural-network"]], "Convolutional Neural Networks": [[3, null]], "Correlation Function and Design/Feature Matrix": [[29, "correlation-function-and-design-feature-matrix"]], "Correlation Matrix": [[11, "correlation-matrix"], [29, "correlation-matrix"]], "Correlation Matrix with Pandas": [[29, "correlation-matrix-with-pandas"]], "Course Format": [[28, "course-format"]], "Course setting": [[24, null]], "Covariance Matrix Examples": [[29, "covariance-matrix-examples"]], "Covariance and Correlation Matrix": [[29, "covariance-and-correlation-matrix"]], "Cross-validation": [[6, "cross-validation"]], "Deadlines for projects (tentative)": [[28, "deadlines-for-projects-tentative"]], "Decision trees, overarching aims": [[9, null]], "Deep Neural Networks": [[31, "deep-neural-networks"]], "Deep learning methods": [[28, "deep-learning-methods"]], "Define model and architecture": [[1, "define-model-and-architecture"]], "Defining the cost function": [[1, "defining-the-cost-function"]], "Definitions": [[19, "definitions"]], "Deliverables": [[15, "deliverables"], [16, "deliverables"], [19, "deliverables"], [20, "deliverables"]], "Derivation of the AdaGrad Algorithm": [[31, "derivation-of-the-adagrad-algorithm"]], "Derivatives and the chain rule": [[12, "derivatives-and-the-chain-rule"]], "Derivatives, example 1": [[29, "derivatives-example-1"]], "Deriving OLS from a probability distribution": [[5, "deriving-ols-from-a-probability-distribution"]], "Deriving and Implementing Ordinary Least Squares": [[16, "deriving-and-implementing-ordinary-least-squares"]], "Deriving and Implementing Ridge Regression": [[17, "deriving-and-implementing-ridge-regression"]], "Deriving the Lasso Regression Equations": [[29, "deriving-the-lasso-regression-equations"], [30, "deriving-the-lasso-regression-equations"], [30, "id6"]], "Deriving the Ridge Regression Equations": [[29, "deriving-the-ridge-regression-equations"], [30, "deriving-the-ridge-regression-equations"], [30, "id3"]], "Deriving the back propagation code for a multilayer perceptron model": [[12, "deriving-the-back-propagation-code-for-a-multilayer-perceptron-model"]], "Developing a code for doing neural networks with back propagation": [[1, "developing-a-code-for-doing-neural-networks-with-back-propagation"]], "Diagonalize the sample covariance matrix to obtain the principal components": [[11, "diagonalize-the-sample-covariance-matrix-to-obtain-the-principal-components"]], "Different kernels and Mercer\u2019s theorem": [[8, "different-kernels-and-mercer-s-theorem"]], "Disadvantages": [[9, "disadvantages"]], "Discriminative Modeling": [[28, "discriminative-modeling"]], "Domains and probabilities": [[25, "domains-and-probabilities"]], "Dropout": [[1, "dropout"]], "Economy-size SVD": [[29, "economy-size-svd"], [30, "economy-size-svd"]], "Elements of Probability Theory and Statistical Data Analysis": [[25, null]], "Empirical Evidence: Convergence Time and Memory in Practice": [[31, "empirical-evidence-convergence-time-and-memory-in-practice"]], "Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods": [[10, null]], "Entropy and the ID3 algorithm": [[9, "entropy-and-the-id3-algorithm"]], "Essential elements of ML": [[28, "essential-elements-of-ml"]], "Evaluate model performance on test data": [[1, "evaluate-model-performance-on-test-data"]], "Example 2": [[29, "example-2"]], "Example 3": [[29, "example-3"]], "Example 4": [[29, "example-4"]], "Example Matrix": [[29, "example-matrix"], [30, "example-matrix"]], "Example of discriminative modeling, taken from Generative Deep Learning by David Foster": [[28, "example-of-discriminative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of generative modeling, taken from Generative Deep Learning by David Foster": [[28, "example-of-generative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of own Standard scaling": [[29, "example-of-own-standard-scaling"]], "Example relevant for the exercises": [[29, "example-relevant-for-the-exercises"]], "Example: Exponential decay": [[2, "example-exponential-decay"]], "Example: Population growth": [[2, "example-population-growth"]], "Example: The diffusion equation": [[2, "example-the-diffusion-equation"]], "Example: binary classification problem": [[1, "example-binary-classification-problem"]], "Examples": [[28, "examples"]], "Examples of likelihood functions used in logistic regression and neural networks": [[7, "examples-of-likelihood-functions-used-in-logistic-regression-and-neural-networks"]], "Exercise 1 - Choice of model and degrees of freedom": [[17, "exercise-1-choice-of-model-and-degrees-of-freedom"]], "Exercise 1 - Finding the derivative of Matrix-Vector expressions": [[16, "exercise-1-finding-the-derivative-of-matrix-vector-expressions"]], "Exercise 1 - Github Setup": [[15, "exercise-1-github-setup"]], "Exercise 1, scale your data": [[18, "exercise-1-scale-your-data"]], "Exercise 1: Creating the report document": [[20, "exercise-1-creating-the-report-document"]], "Exercise 1: Expectation values for ordinary least squares expressions": [[19, "exercise-1-expectation-values-for-ordinary-least-squares-expressions"]], "Exercise 1: Setting up various Python environments": [[0, "exercise-1-setting-up-various-python-environments"]], "Exercise 2 - Deriving the expression for OLS": [[16, "exercise-2-deriving-the-expression-for-ols"]], "Exercise 2 - Deriving the expression for Ridge Regression": [[17, "exercise-2-deriving-the-expression-for-ridge-regression"]], "Exercise 2 - Setting up a Github repository": [[15, "exercise-2-setting-up-a-github-repository"]], "Exercise 2, calculate the gradients": [[18, "exercise-2-calculate-the-gradients"]], "Exercise 2: Adding good figures": [[20, "exercise-2-adding-good-figures"]], "Exercise 2: Expectation values for Ridge regression": [[19, "exercise-2-expectation-values-for-ridge-regression"]], "Exercise 2: making your own data and exploring scikit-learn": [[0, "exercise-2-making-your-own-data-and-exploring-scikit-learn"]], "Exercise 3 - Creating feature matrix and implementing OLS using the analytical expression": [[16, "exercise-3-creating-feature-matrix-and-implementing-ols-using-the-analytical-expression"]], "Exercise 3 - Fitting an OLS model to data": [[15, "exercise-3-fitting-an-ols-model-to-data"]], "Exercise 3 - Scaling data": [[17, "exercise-3-scaling-data"]], "Exercise 3 - Setting up a Python virtual environment": [[15, "exercise-3-setting-up-a-python-virtual-environment"]], "Exercise 3, using the analytical formulae for OLS and Ridge regression to find the optimal paramters \\boldsymbol{\\theta}": [[18, "exercise-3-using-the-analytical-formulae-for-ols-and-ridge-regression-to-find-the-optimal-paramters-boldsymbol-theta"]], "Exercise 3: Deriving the expression for the Bias-Variance Trade-off": [[19, "exercise-3-deriving-the-expression-for-the-bias-variance-trade-off"]], "Exercise 3: Normalizing our data": [[0, "exercise-3-normalizing-our-data"]], "Exercise 3: Writing an abstract and introduction": [[20, "exercise-3-writing-an-abstract-and-introduction"]], "Exercise 4 - Fitting a polynomial": [[16, "exercise-4-fitting-a-polynomial"]], "Exercise 4 - Implementing Ridge Regression": [[17, "exercise-4-implementing-ridge-regression"]], "Exercise 4 - Testing multiple hyperparameters": [[17, "exercise-4-testing-multiple-hyperparameters"]], "Exercise 4 - The train-test split": [[15, "exercise-4-the-train-test-split"]], "Exercise 4, Implementing the simplest form for gradient descent": [[18, "exercise-4-implementing-the-simplest-form-for-gradient-descent"]], "Exercise 4: Adding Ridge Regression": [[0, "exercise-4-adding-ridge-regression"]], "Exercise 4: Computing the Bias and Variance": [[19, "exercise-4-computing-the-bias-and-variance"]], "Exercise 4: Making the code avaliable and presentable": [[20, "exercise-4-making-the-code-avaliable-and-presentable"]], "Exercise 5 - Comparing your code with sklearn": [[16, "exercise-5-comparing-your-code-with-sklearn"]], "Exercise 5, Ridge regression and a new Synthetic Dataset": [[18, "exercise-5-ridge-regression-and-a-new-synthetic-dataset"]], "Exercise 5: Analytical exercises": [[0, "exercise-5-analytical-exercises"]], "Exercise 5: Interpretation of scaling and metrics": [[19, "exercise-5-interpretation-of-scaling-and-metrics"]], "Exercise 5: Referencing": [[20, "exercise-5-referencing"]], "Exercise: Cross-validation as resampling techniques, adding more complexity": [[6, "exercise-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Exercise: Analysis of real data": [[6, "exercise-analysis-of-real-data"]], "Exercise: Bias-variance trade-off and resampling techniques": [[6, "exercise-bias-variance-trade-off-and-resampling-techniques"]], "Exercise: Lasso Regression on the Franke function with resampling": [[6, "exercise-lasso-regression-on-the-franke-function-with-resampling"]], "Exercise: Ordinary Least Square (OLS) on the Franke function": [[6, "exercise-ordinary-least-square-ols-on-the-franke-function"]], "Exercise: Ridge Regression on the Franke function with resampling": [[6, "exercise-ridge-regression-on-the-franke-function-with-resampling"]], "Exercises": [[0, "exercises"]], "Exercises and Projects": [[6, "exercises-and-projects"]], "Exercises week 34": [[15, null]], "Exercises week 35": [[16, null]], "Exercises week 36": [[17, null]], "Exercises week 37": [[18, null]], "Exercises week 38": [[19, null]], "Exercises week 39": [[20, null]], "Expectation values": [[25, "expectation-values"]], "Extending to more than one variable": [[30, "extending-to-more-than-one-variable"]], "Extremely useful tools, strongly recommended": [[28, "extremely-useful-tools-strongly-recommended"]], "Feed-forward neural networks": [[12, "feed-forward-neural-networks"]], "Feed-forward pass": [[1, "feed-forward-pass"]], "Final back propagating equation": [[12, "final-back-propagating-equation"]], "Fine-tuning neural network hyperparameters": [[1, "fine-tuning-neural-network-hyperparameters"]], "Fitting an Equation of State for Dense Nuclear Matter": [[0, "fitting-an-equation-of-state-for-dense-nuclear-matter"]], "Fixing the singularity": [[29, "fixing-the-singularity"], [30, "fixing-the-singularity"]], "Format for electronic delivery of report and programs": [[23, "format-for-electronic-delivery-of-report-and-programs"]], "Frequently used scaling functions": [[29, "frequently-used-scaling-functions"], [31, "frequently-used-scaling-functions"]], "From OLS to Ridge and Lasso": [[30, "from-ols-to-ridge-and-lasso"]], "From one to many layers, the universal approximation theorem": [[12, "from-one-to-many-layers-the-universal-approximation-theorem"]], "Functionality in Scikit-Learn": [[29, "functionality-in-scikit-learn"], [31, "functionality-in-scikit-learn"]], "Further Dimensionality Remarks": [[3, "further-dimensionality-remarks"]], "Further properties (important for our analyses later)": [[5, "further-properties-important-for-our-analyses-later"], [29, "further-properties-important-for-our-analyses-later"], [30, "further-properties-important-for-our-analyses-later"]], "Gaussian Elimination": [[22, "gaussian-elimination"]], "General Features": [[9, "general-features"]], "General linear models and linear algebra": [[28, "general-linear-models-and-linear-algebra"]], "Generalizing the fitting procedure as a linear algebra problem": [[28, "generalizing-the-fitting-procedure-as-a-linear-algebra-problem"], [28, "id1"]], "Generative Adversarial Networks": [[4, "generative-adversarial-networks"]], "Generative Models": [[4, "generative-models"]], "Generative Versus Discriminative Modeling": [[28, "generative-versus-discriminative-modeling"]], "Geometric Interpretation and link with Singular Value Decomposition": [[11, "geometric-interpretation-and-link-with-singular-value-decomposition"]], "Getting started with project 1": [[20, "getting-started-with-project-1"]], "Gradient Boosting, Classification Example": [[10, "gradient-boosting-classification-example"]], "Gradient Boosting, Examples of Regression": [[10, "gradient-boosting-examples-of-regression"]], "Gradient Clipping": [[1, "gradient-clipping"]], "Gradient Descent Example": [[30, "id1"], [31, "id1"]], "Gradient boosting: Basics with Steepest Descent/Functional Gradient Descent": [[10, "gradient-boosting-basics-with-steepest-descent-functional-gradient-descent"]], "Gradient descent": [[2, "gradient-descent"]], "Gradient descent and Ridge": [[30, "gradient-descent-and-ridge"], [31, "gradient-descent-and-ridge"]], "Gradient descent and revisiting Ordinary Least Squares from last week": [[31, "gradient-descent-and-revisiting-ordinary-least-squares-from-last-week"]], "Gradient descent example": [[30, "gradient-descent-example"], [31, "gradient-descent-example"]], "Grading": [[26, "grading"], [26, "id2"], [28, "grading"]], "How to take derivatives of Matrix-Vector expressions": [[16, "how-to-take-derivatives-of-matrix-vector-expressions"]], "Hyperplanes and all that": [[8, "hyperplanes-and-all-that"]], "Important Matrix and vector handling packages": [[22, "important-matrix-and-vector-handling-packages"]], "Important technicalities: More on Rescaling data": [[29, "important-technicalities-more-on-rescaling-data"]], "Improving gradient descent with momentum": [[31, "improving-gradient-descent-with-momentum"]], "Improving performance": [[1, "improving-performance"]], "In summary": [[26, "in-summary"]], "Including Stochastic Gradient Descent with Autograd": [[13, "including-stochastic-gradient-descent-with-autograd"], [31, "including-stochastic-gradient-descent-with-autograd"]], "Incremental PCA": [[11, "incremental-pca"]], "Installing R, C++, cython or Julia": [[28, "installing-r-c-cython-or-julia"]], "Installing R, C++, cython, Numba etc": [[28, "installing-r-c-cython-numba-etc"]], "Instructor information": [[26, "instructor-information"]], "Interpretations and optimizing our parameters": [[28, "interpretations-and-optimizing-our-parameters"], [28, "id2"], [28, "id3"], [29, "interpretations-and-optimizing-our-parameters"], [29, "id1"], [29, "id2"]], "Interpreting the Ridge results": [[29, "interpreting-the-ridge-results"], [30, "interpreting-the-ridge-results"], [30, "id4"]], "Introducing JAX": [[13, "introducing-jax"]], "Introducing the Covariance and Correlation functions": [[11, "introducing-the-covariance-and-correlation-functions"], [29, "introducing-the-covariance-and-correlation-functions"]], "Introduction": [[0, "introduction"], [6, "introduction"], [21, "introduction"], [22, "introduction"]], "Introduction to numerical projects": [[23, "introduction-to-numerical-projects"]], "Iterative Fitting, Classification and AdaBoost": [[10, "iterative-fitting-classification-and-adaboost"]], "Iterative Fitting, Regression and Squared-error Cost Function": [[10, "iterative-fitting-regression-and-squared-error-cost-function"]], "Kernel PCA": [[11, "kernel-pca"]], "Kernels and non-linearity": [[8, "kernels-and-non-linearity"]], "LU Decomposition, the inverse of a matrix": [[22, "lu-decomposition-the-inverse-of-a-matrix"]], "Lasso Regression": [[30, "lasso-regression"]], "Lasso case": [[30, "lasso-case"]], "Layers": [[1, "layers"]], "Layers used to build CNNs": [[3, "layers-used-to-build-cnns"]], "Learning goals": [[15, "learning-goals"], [16, "learning-goals"], [17, "learning-goals"], [18, "learning-goals"], [19, "learning-goals"], [20, "learning-goals"]], "Learning outcomes": [[21, "learning-outcomes"], [28, "learning-outcomes"]], "Lectures and ComputerLab": [[28, "lectures-and-computerlab"]], "Limitations of supervised learning with deep networks": [[1, "limitations-of-supervised-learning-with-deep-networks"]], "Linear Algebra, Handling of Arrays and more Python Features": [[22, null]], "Linear Regression": [[0, null]], "Linear Regression Problems": [[29, "linear-regression-problems"], [30, "linear-regression-problems"]], "Linear Regression and the SVD": [[30, "linear-regression-and-the-svd"]], "Linear Regression, basic elements": [[0, "linear-regression-basic-elements"]], "Linking Bayes\u2019 Theorem with Ridge and Lasso Regression": [[5, "linking-bayes-theorem-with-ridge-and-lasso-regression"]], "Linking the regression analysis with a statistical interpretation": [[5, "linking-the-regression-analysis-with-a-statistical-interpretation"]], "Linking with the SVD": [[5, "linking-with-the-svd"], [29, "linking-with-the-svd"]], "Links to relevant courses at the University of Oslo": [[27, "links-to-relevant-courses-at-the-university-of-oslo"]], "Logistic Regression": [[7, null], [7, "id1"]], "MNIST and GANs": [[4, "mnist-and-gans"]], "Machine Learning": [[28, "machine-learning"]], "Machine learning": [[21, "machine-learning"]], "Main textbooks": [[28, "main-textbooks"]], "Making a tree": [[9, "making-a-tree"]], "Making your own Bootstrap: Changing the Level of the Decision Tree": [[10, "making-your-own-bootstrap-changing-the-level-of-the-decision-tree"]], "Making your own test-train splitting": [[29, "making-your-own-test-train-splitting"]], "Material for exercises week 35": [[29, "material-for-exercises-week-35"]], "Material for lab sessions sessions Tuesday and Wednesday": [[30, "material-for-lab-sessions-sessions-tuesday-and-wednesday"]], "Material for lecture Monday September 2": [[30, "material-for-lecture-monday-september-2"]], "Material for lecture Monday September 8": [[31, "material-for-lecture-monday-september-8"]], "Material for the lab sessions": [[31, "material-for-the-lab-sessions"]], "Mathematical Interpretation of Ordinary Least Squares": [[5, "mathematical-interpretation-of-ordinary-least-squares"], [29, "mathematical-interpretation-of-ordinary-least-squares"], [30, "mathematical-interpretation-of-ordinary-least-squares"]], "Mathematical optimization of convex functions": [[8, "mathematical-optimization-of-convex-functions"]], "Mathematics of CNNs": [[3, "mathematics-of-cnns"]], "Mathematics of the SVD and implications": [[5, "mathematics-of-the-svd-and-implications"], [29, "mathematics-of-the-svd-and-implications"], [30, "mathematics-of-the-svd-and-implications"]], "Matrices in Python": [[28, "matrices-in-python"]], "Matrix multiplication": [[1, "matrix-multiplication"]], "Matrix-vector notation and activation": [[12, "matrix-vector-notation-and-activation"]], "Meet the covariance!": [[25, "meet-the-covariance"]], "Meet the Covariance Matrix": [[5, "meet-the-covariance-matrix"], [29, "meet-the-covariance-matrix"]], "Meet the Hessian Matrix": [[29, "meet-the-hessian-matrix"]], "Meet the Pandas": [[28, "meet-the-pandas"]], "Memory Usage and Scalability": [[31, "memory-usage-and-scalability"]], "Memory constraints": [[31, "memory-constraints"]], "Min-Max Scaling": [[29, "min-max-scaling"]], "Momentum based GD": [[13, "momentum-based-gd"], [31, "momentum-based-gd"]], "More complicated Example: The Ising model": [[6, "more-complicated-example-the-ising-model"]], "More interpretations": [[29, "more-interpretations"], [30, "more-interpretations"], [30, "id5"]], "More on Dimensionalities": [[3, "more-on-dimensionalities"]], "More on Rescaling data": [[6, "more-on-rescaling-data"]], "More on Steepest descent": [[30, "more-on-steepest-descent"]], "More on convex functions": [[30, "more-on-convex-functions"]], "More preprocessing": [[29, "more-preprocessing"], [31, "more-preprocessing"]], "Motivation for Adaptive Step Sizes": [[31, "motivation-for-adaptive-step-sizes"]], "Multilayer perceptrons": [[12, "multilayer-perceptrons"]], "Network requirements": [[2, "network-requirements"]], "Neural Networks vs CNNs": [[3, "neural-networks-vs-cnns"]], "Neural networks": [[12, null]], "Non-Convex Problems": [[31, "non-convex-problems"]], "Note about SVD Calculations": [[29, "note-about-svd-calculations"], [30, "note-about-svd-calculations"]], "Note on Scikit-Learn": [[30, "note-on-scikit-learn"]], "Numerical experiments and the covariance, central limit theorem": [[25, "numerical-experiments-and-the-covariance-central-limit-theorem"]], "Numpy and arrays": [[22, "numpy-and-arrays"], [28, "numpy-and-arrays"]], "Numpy examples and Important Matrix and vector handling packages": [[28, "numpy-examples-and-important-matrix-and-vector-handling-packages"]], "Optimization and gradient descent, the central part of any Machine Learning algortithm": [[30, "optimization-and-gradient-descent-the-central-part-of-any-machine-learning-algortithm"]], "Optimization, the central part of any Machine Learning algortithm": [[13, null]], "Optimizing our parameters": [[28, "optimizing-our-parameters"]], "Optimizing our parameters, more details": [[28, "optimizing-our-parameters-more-details"]], "Optimizing the cost function": [[1, "optimizing-the-cost-function"]], "Organizing our data": [[0, "organizing-our-data"], [28, "organizing-our-data"]], "Other Matrix and Vector Operations": [[22, "other-matrix-and-vector-operations"]], "Other Types of Recurrent Neural Networks": [[4, "other-types-of-recurrent-neural-networks"]], "Other courses on Data science and Machine Learning at UiO": [[28, "other-courses-on-data-science-and-machine-learning-at-uio"]], "Other courses on Data science and Machine Learning at UiO, contn": [[28, "other-courses-on-data-science-and-machine-learning-at-uio-contn"]], "Other popular texts": [[28, "other-popular-texts"]], "Other techniques": [[11, "other-techniques"]], "Other types of networks": [[12, "other-types-of-networks"]], "Other ways of visualizing the trees": [[9, "other-ways-of-visualizing-the-trees"]], "Our model for the nuclear binding energies": [[28, "our-model-for-the-nuclear-binding-energies"]], "Overview of first week": [[28, "overview-of-first-week"]], "Overview video on Stochastic Gradient Descent (SGD)": [[31, "overview-video-on-stochastic-gradient-descent-sgd"]], "Own code for Ordinary Least Squares": [[28, "own-code-for-ordinary-least-squares"], [29, "own-code-for-ordinary-least-squares"]], "PCA and scikit-learn": [[11, "pca-and-scikit-learn"]], "Pandas AI": [[28, "pandas-ai"]], "Part a : Ordinary Least Square (OLS) for the Runge function": [[23, "part-a-ordinary-least-square-ols-for-the-runge-function"]], "Part b: Adding Ridge regression for the Runge function": [[23, "part-b-adding-ridge-regression-for-the-runge-function"]], "Part c: Writing your own gradient descent code": [[23, "part-c-writing-your-own-gradient-descent-code"]], "Part d: Including momentum and more advanced ways to update the learning the rate": [[23, "part-d-including-momentum-and-more-advanced-ways-to-update-the-learning-the-rate"]], "Part e: Writing our own code for Lasso regression": [[23, "part-e-writing-our-own-code-for-lasso-regression"]], "Part f: Stochastic gradient descent": [[23, "part-f-stochastic-gradient-descent"]], "Part g: Bias-variance trade-off and resampling techniques": [[23, "part-g-bias-variance-trade-off-and-resampling-techniques"]], "Part h): Cross-validation as resampling techniques, adding more complexity": [[23, "part-h-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Partial Differential Equations": [[2, "partial-differential-equations"]], "Plans for week 35": [[29, "plans-for-week-35"]], "Plans for week 36": [[30, "plans-for-week-36"]], "Plans for week 37, lecture Monday": [[31, "plans-for-week-37-lecture-monday"]], "Practical tips": [[13, "practical-tips"], [31, "practical-tips"]], "Practicalities": [[26, "practicalities"], [26, "id1"]], "Preamble: Note on writing reports, using reference material, AI and other tools": [[23, "preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools"]], "Predicting New Points With A Trained Recurrent Neural Network": [[4, "predicting-new-points-with-a-trained-recurrent-neural-network"]], "Preprocessing our data": [[29, "preprocessing-our-data"]], "Prerequisites": [[28, "prerequisites"]], "Prerequisites and background": [[21, "prerequisites-and-background"]], "Prerequisites: Collect and pre-process data": [[3, "prerequisites-collect-and-pre-process-data"]], "Probability Distribution Functions": [[25, "probability-distribution-functions"]], "Program example for gradient descent with Ridge Regression": [[30, "program-example-for-gradient-descent-with-ridge-regression"], [31, "program-example-for-gradient-descent-with-ridge-regression"]], "Program for stochastic gradient": [[13, "program-for-stochastic-gradient"]], "Project 1 on Machine Learning, deadline October 6 (midnight), 2025": [[23, null]], "Properties of PDFs": [[25, "properties-of-pdfs"]], "Pros and cons": [[31, "pros-and-cons"]], "Pros and cons of trees, pros": [[9, "pros-and-cons-of-trees-pros"]], "Python installers": [[21, "python-installers"], [28, "python-installers"]], "RMS prop": [[13, "rms-prop"]], "RMSProp algorithm, taken from Goodfellow et al": [[31, "rmsprop-algorithm-taken-from-goodfellow-et-al"]], "RMSProp: Adaptive Learning Rates": [[31, "rmsprop-adaptive-learning-rates"]], "RMSprop for adaptive learning rate with Stochastic Gradient Descent": [[31, "rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent"]], "Random Numbers": [[25, "random-numbers"]], "Random forests": [[10, "random-forests"]], "Randomized PCA": [[11, "randomized-pca"]], "Reading material": [[28, "reading-material"]], "Reading recommendations:": [[29, "reading-recommendations"]], "Reading suggestions week 34": [[28, "reading-suggestions-week-34"]], "Readings and Videos:": [[31, "readings-and-videos"]], "Recurrent neural networks": [[12, "recurrent-neural-networks"]], "Recurrent neural networks: Overarching view": [[4, null]], "Reducing the number of degrees of freedom, overarching view": [[0, "reducing-the-number-of-degrees-of-freedom-overarching-view"], [29, "reducing-the-number-of-degrees-of-freedom-overarching-view"]], "Reformulating the problem": [[2, "reformulating-the-problem"]], "Regression Case": [[10, "regression-case"]], "Regression analysis and resampling methods": [[23, "regression-analysis-and-resampling-methods"]], "Regression analysis, overarching aims": [[28, "regression-analysis-overarching-aims"]], "Regression analysis, overarching aims II": [[28, "regression-analysis-overarching-aims-ii"]], "Regularization": [[1, "regularization"]], "Reminder from last week": [[29, "reminder-from-last-week"]], "Reminder on Newton-Raphson\u2019s method": [[30, "reminder-on-newton-raphson-s-method"]], "Reminder on Statistics": [[6, "reminder-on-statistics"]], "Reminder on different scaling methods": [[31, "reminder-on-different-scaling-methods"]], "Replace or not": [[13, "replace-or-not"], [31, "replace-or-not"]], "Required Technologies": [[21, "required-technologies"]], "Resampling Methods": [[6, null]], "Resampling and the Bias-Variance Trade-off": [[19, "resampling-and-the-bias-variance-trade-off"]], "Resampling methods": [[6, "id1"]], "Residual Error": [[29, "residual-error"], [30, "residual-error"]], "Resources on differential equations and deep learning": [[2, "resources-on-differential-equations-and-deep-learning"]], "Revisiting Ordinary Least Squares": [[30, "revisiting-ordinary-least-squares"]], "Revisiting our Linear Regression Solvers": [[13, "revisiting-our-linear-regression-solvers"]], "Rewriting the Covariance and/or Correlation Matrix": [[29, "rewriting-the-covariance-and-or-correlation-matrix"]], "Rewriting the fitting procedure as a linear algebra problem": [[28, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem"]], "Rewriting the fitting procedure as a linear algebra problem, more details": [[28, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem-more-details"]], "Ridge Regression": [[30, "ridge-regression"]], "Ridge and LASSO Regression": [[29, "ridge-and-lasso-regression"], [30, "ridge-and-lasso-regression"], [30, "id2"]], "Ridge and Lasso Regression": [[5, null], [5, "id1"]], "SGD example": [[31, "sgd-example"]], "SGD vs Full-Batch GD: Convergence Speed and Memory Comparison": [[31, "sgd-vs-full-batch-gd-convergence-speed-and-memory-comparison"]], "SVD analysis": [[30, "svd-analysis"]], "Same code but now with momentum gradient descent": [[13, "same-code-but-now-with-momentum-gradient-descent"], [31, "same-code-but-now-with-momentum-gradient-descent"], [31, "id3"], [31, "id4"]], "Schedule first week": [[28, "schedule-first-week"]], "Schematic Regression Procedure": [[9, "schematic-regression-procedure"]], "Second moment of the gradient": [[31, "second-moment-of-the-gradient"]], "September 15-19": [[19, "september-15-19"]], "Setting up the Back propagation algorithm": [[12, "setting-up-the-back-propagation-algorithm"]], "Setting up the Matrix to be inverted": [[29, "setting-up-the-matrix-to-be-inverted"], [30, "setting-up-the-matrix-to-be-inverted"]], "Setting up the network using Autograd; The full program": [[2, "setting-up-the-network-using-autograd-the-full-program"]], "Similar (second order function now) problem but now with AdaGrad": [[13, "similar-second-order-function-now-problem-but-now-with-adagrad"], [31, "similar-second-order-function-now-problem-but-now-with-adagrad"]], "Simple Python Code to read in Data and perform Classification": [[9, "simple-python-code-to-read-in-data-and-perform-classification"]], "Simple case": [[29, "simple-case"], [30, "simple-case"]], "Simple code for solving the above problem": [[30, "simple-code-for-solving-the-above-problem"]], "Simple example code": [[31, "simple-example-code"]], "Simple example to illustrate Ordinary Least Squares, Ridge and Lasso Regression": [[30, "simple-example-to-illustrate-ordinary-least-squares-ridge-and-lasso-regression"]], "Simple geometric interpretation": [[30, "simple-geometric-interpretation"]], "Simple linear regression model using scikit-learn": [[0, "simple-linear-regression-model-using-scikit-learn"], [28, "simple-linear-regression-model-using-scikit-learn"]], "Simple one-dimensional second-order polynomial": [[18, "simple-one-dimensional-second-order-polynomial"]], "Simple program": [[30, "simple-program"], [31, "simple-program"]], "Slightly different approach": [[31, "slightly-different-approach"]], "Sneaking in automatic differentiation using Autograd": [[31, "sneaking-in-automatic-differentiation-using-autograd"]], "Software and needed installations": [[23, "software-and-needed-installations"], [28, "software-and-needed-installations"]], "Solving Differential Equations with Deep Learning": [[2, null]], "Solving the one dimensional Poisson equation": [[2, "solving-the-one-dimensional-poisson-equation"]], "Solving the wave equation with Neural Networks": [[2, "solving-the-wave-equation-with-neural-networks"]], "Some famous Matrices": [[22, "some-famous-matrices"]], "Some simple problems": [[13, "some-simple-problems"], [30, "some-simple-problems"]], "Some useful matrix and vector expressions": [[29, "some-useful-matrix-and-vector-expressions"]], "Splitting our Data in Training and Test data": [[0, "splitting-our-data-in-training-and-test-data"], [29, "splitting-our-data-in-training-and-test-data"]], "Standard steepest descent": [[13, "standard-steepest-descent"]], "Statistical analysis and optimization of data": [[21, "statistical-analysis-and-optimization-of-data"], [28, "statistical-analysis-and-optimization-of-data"]], "Steepest descent": [[13, "steepest-descent"], [30, "steepest-descent"]], "Stochastic Gradient Descent": [[31, "stochastic-gradient-descent"]], "Stochastic Gradient Descent (SGD)": [[13, "stochastic-gradient-descent-sgd"], [31, "stochastic-gradient-descent-sgd"]], "Stochastic variables and the main concepts, the discrete case": [[25, "stochastic-variables-and-the-main-concepts-the-discrete-case"]], "Strongly Convex Case": [[31, "strongly-convex-case"]], "Support Vector Machines, overarching aims": [[8, null]], "Systematic reduction": [[3, "systematic-reduction"]], "Teachers": [[28, "teachers"]], "Teachers and Grading": [[26, null]], "Teaching Assistants Fall semester 2023": [[26, "teaching-assistants-fall-semester-2023"]], "Tentative deadllines for projects": [[26, "tentative-deadllines-for-projects"]], "Testing the Means Squared Error as function of Complexity": [[0, "testing-the-means-squared-error-as-function-of-complexity"], [29, "testing-the-means-squared-error-as-function-of-complexity"]], "Textbooks": [[27, null]], "The Algorithm before theorem": [[11, "the-algorithm-before-theorem"]], "The Breast Cancer Data, now with Keras": [[1, "the-breast-cancer-data-now-with-keras"]], "The CART algorithm for Classification": [[9, "the-cart-algorithm-for-classification"]], "The CART algorithm for Regression": [[9, "the-cart-algorithm-for-regression"]], "The CIFAR01 data set": [[3, "the-cifar01-data-set"]], "The Hessian matrix": [[30, "the-hessian-matrix"], [31, "the-hessian-matrix"]], "The Hessian matrix for Ridge Regression": [[30, "the-hessian-matrix-for-ridge-regression"], [31, "the-hessian-matrix-for-ridge-regression"]], "The Jacobian": [[29, "the-jacobian"]], "The MNIST dataset again": [[3, "the-mnist-dataset-again"]], "The OLS case": [[30, "the-ols-case"]], "The RELU function family": [[1, "the-relu-function-family"]], "The Ridge case": [[30, "the-ridge-case"]], "The SVD, a Fantastic Algorithm": [[29, "the-svd-a-fantastic-algorithm"], [30, "the-svd-a-fantastic-algorithm"]], "The Softmax function": [[1, "the-softmax-function"]], "The \\chi^2 function": [[0, "the-chi-2-function"], [28, "the-chi-2-function"], [28, "id4"], [28, "id5"], [28, "id6"], [28, "id7"], [28, "id8"]], "The bias-variance tradeoff": [[6, "the-bias-variance-tradeoff"]], "The code for solving the ODE": [[2, "the-code-for-solving-the-ode"]], "The complete code with a simple data set": [[29, "the-complete-code-with-a-simple-data-set"]], "The cost/loss function": [[29, "the-cost-loss-function"]], "The course has two central parts": [[21, "the-course-has-two-central-parts"]], "The derivative of the cost/loss function": [[30, "the-derivative-of-the-cost-loss-function"], [31, "the-derivative-of-the-cost-loss-function"]], "The equations": [[30, "the-equations"]], "The equations for ordinary least squares": [[29, "the-equations-for-ordinary-least-squares"]], "The first Case": [[30, "the-first-case"]], "The gradient step": [[31, "the-gradient-step"]], "The ideal": [[30, "the-ideal"]], "The logistic function": [[7, "the-logistic-function"]], "The mean squared error and its derivative": [[29, "the-mean-squared-error-and-its-derivative"]], "The moons example": [[8, "the-moons-example"]], "The multilayer perceptron (MLP)": [[12, "the-multilayer-perceptron-mlp"]], "The network with one input layer, specified number of hidden layers, and one output layer": [[2, "the-network-with-one-input-layer-specified-number-of-hidden-layers-and-one-output-layer"]], "The plethora of machine learning algorithms/methods": [[28, "the-plethora-of-machine-learning-algorithms-methods"]], "The sensitiveness of the gradient descent": [[30, "the-sensitiveness-of-the-gradient-descent"]], "The singular value decomposition": [[5, "the-singular-value-decomposition"], [29, "the-singular-value-decomposition"], [30, "the-singular-value-decomposition"]], "The two-dimensional case": [[8, "the-two-dimensional-case"]], "Theoretical Convergence Speed and convex optimization": [[31, "theoretical-convergence-speed-and-convex-optimization"]], "Time decay rate": [[31, "time-decay-rate"]], "To our real data: nuclear binding energies. Brief reminder on masses and binding energies": [[28, "to-our-real-data-nuclear-binding-energies-brief-reminder-on-masses-and-binding-energies"]], "Topics covered in this course: Statistical analysis and optimization of data": [[28, "topics-covered-in-this-course-statistical-analysis-and-optimization-of-data"]], "Towards the PCA theorem": [[11, "towards-the-pca-theorem"]], "Train and test datasets": [[1, "train-and-test-datasets"]], "Two-dimensional Objects": [[3, "two-dimensional-objects"]], "Type of problem": [[2, "type-of-problem"]], "Types of Machine Learning": [[28, "types-of-machine-learning"]], "Use the books!": [[19, "use-the-books"]], "Useful Python libraries": [[21, "useful-python-libraries"], [28, "useful-python-libraries"]], "Using Autograd": [[13, "using-autograd"]], "Using forward Euler to solve the ODE": [[2, "using-forward-euler-to-solve-the-ode"]], "Using gradient descent methods, limitations": [[13, "using-gradient-descent-methods-limitations"], [30, "using-gradient-descent-methods-limitations"], [31, "using-gradient-descent-methods-limitations"]], "Visualization": [[1, "visualization"], [1, "id1"]], "Visualizing the Tree, Classification": [[9, "visualizing-the-tree-classification"]], "Week 34: Introduction to the course, Logistics and Practicalities": [[28, null]], "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression": [[29, null]], "Week 36: Linear Regression and Gradient descent": [[30, null]], "Week 37: Gradient descent methods": [[31, null]], "What Is Generative Modeling?": [[28, "what-is-generative-modeling"]], "What does it mean?": [[29, "what-does-it-mean"], [30, "what-does-it-mean"]], "What is Machine Learning?": [[0, "what-is-machine-learning"]], "What is a good model?": [[0, "what-is-a-good-model"], [28, "what-is-a-good-model"]], "What is a good model? Can we define it?": [[28, "what-is-a-good-model-can-we-define-it"]], "When do we stop?": [[31, "when-do-we-stop"]], "Which activation function should I use?": [[1, "which-activation-function-should-i-use"]], "Why Combine Momentum and RMSProp?": [[31, "why-combine-momentum-and-rmsprop"]], "Why Linear Regression (aka Ordinary Least Squares and family)": [[28, "why-linear-regression-aka-ordinary-least-squares-and-family"]], "Wisconsin Cancer Data": [[7, "wisconsin-cancer-data"]], "With Lasso Regression": [[30, "with-lasso-regression"]], "Writing Our First Generative Adversarial Network": [[4, "writing-our-first-generative-adversarial-network"]], "Writing our own PCA code": [[11, "writing-our-own-pca-code"]], "Writing the Cost Function": [[30, "writing-the-cost-function"]], "XGBoost: Extreme Gradient Boosting": [[10, "xgboost-extreme-gradient-boosting"]], "Yet another Example": [[30, "yet-another-example"]], "a) Expression for Ridge regression": [[17, "a-expression-for-ridge-regression"]], "scikit-learn implementation": [[1, "scikit-learn-implementation"]]}, "docnames": ["chapter1", "chapter10", "chapter11", "chapter12", "chapter13", "chapter2", "chapter3", "chapter4", "chapter5", "chapter6", "chapter7", "chapter8", "chapter9", "chapteroptimization", "clustering", "exercisesweek34", "exercisesweek35", "exercisesweek36", "exercisesweek37", "exercisesweek38", "exercisesweek39", "intro", "linalg", "project1", "schedule", "statistics", "teachers", "textbooks", "week34", "week35", "week36", "week37"], "envversion": {"sphinx": 62, "sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "sphinx.ext.intersphinx": 1}, "filenames": ["chapter1.ipynb", "chapter10.ipynb", "chapter11.ipynb", "chapter12.ipynb", "chapter13.ipynb", "chapter2.ipynb", "chapter3.ipynb", "chapter4.ipynb", "chapter5.ipynb", "chapter6.ipynb", "chapter7.ipynb", "chapter8.ipynb", "chapter9.ipynb", "chapteroptimization.ipynb", "clustering.ipynb", "exercisesweek34.ipynb", "exercisesweek35.ipynb", "exercisesweek36.ipynb", "exercisesweek37.ipynb", "exercisesweek38.ipynb", "exercisesweek39.ipynb", "intro.md", "linalg.ipynb", "project1.ipynb", "schedule.md", "statistics.ipynb", "teachers.md", "textbooks.md", "week34.ipynb", "week35.ipynb", "week36.ipynb", "week37.ipynb"], "indexentries": {}, "objects": {}, "objnames": {}, "objtypes": {}, "terms": {"": [0, 1, 2, 3, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 26, 28, 29, 30, 31], "00": [0, 1, 5, 11, 28, 29], "000": [1, 3], "000000": [], "00000000e": [], "001": [2, 8, 13, 30, 31], "004": 5, "004113634617443131": 29, "004113634617443139": 29, "00411363461744314": 29, "004113634617443147": 29, "005b82": [], "00622f": [], "00727646693": [0, 28], "0072b2": [], "00749c": [], "008561": [], "0086649156": [0, 28], "00e0e0": [], "01": [0, 1, 2, 5, 9, 11, 13, 17, 27, 28, 29, 31], "010726": [], "0110": 25, "01719003e": [], "02": [0, 4, 7, 12, 28], "02334824": [], "023b95": [], "024c1a": [], "02857": 4, "02f": 6, "03077640549": 4, "03097597e": [], "031": 5, "04": 11, "0458": 9, "05": [4, 6], "0550ae": [], "062292565": 4, "062435": [], "06730814": [], "07": [], "0713": [0, 28], "07285": 3, "08": 25, "08078025e": [], "080808": [], "08336233266": 4, "08376632": 29, "083766322923899": 29, "0837663229239043": 29, "0917": 9, "0969da4a": [], "0d1117": [], "0n": [0, 28], "0x113e21950": 17, "1": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 24, 25, 26, 27, 28, 30, 31], "10": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 22, 24, 25, 26, 28, 29, 30, 31], "100": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 22, 25, 26, 28, 29, 30, 31], "1000": [0, 1, 2, 4, 5, 8, 11, 13, 14, 18, 19, 21, 25, 28, 30, 31], "10000": [2, 5, 6, 10, 11, 13, 25], "100000": 8, "10001": 10, "1001": 25, "1002": 25, "1003": 25, "1005": 25, "1009": 25, "101": 16, "1011": 25, "1013": 25, "1013904243": 25, "1015": 25, "102": 16, "1023": 25, "1024": 3, "1026": 25, "1027": 25, "103": 1, "1030": 25, "1037": 25, "1038": 25, "1040": 25, "1047": 25, "107": 16, "108": [], "10th": 9, "10x": [0, 28], "11": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 22, 23, 25, 27, 28, 29, 30, 31], "110": [], "1100": 25, "1101": 25, "111": [1, 7, 12], "112": 16, "11340253": [], "11590451": [], "116": 16, "116329": [], "116633": [], "117": 16, "118": 16, "12": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 18, 22, 25, 27, 28, 29, 30, 31], "120": 3, "121": [8, 9, 10, 16], "1215pm": [26, 28], "122": [8, 9, 10], "124": [0, 28], "125": 16, "127": [4, 16], "128": [3, 4, 13, 31], "129": 16, "1298": 9, "12pm": [26, 28], "13": [0, 2, 9, 12, 22, 25, 28], "131": 16, "133": 7, "135": 16, "136": 16, "14": [0, 2, 4, 6, 8, 9, 10, 12, 22, 25, 27, 29], "141": 16, "1412": 31, "141414": [], "143": 16, "1446729567": 4, "149": 16, "14g": 6, "15": [0, 2, 4, 6, 7, 8, 9, 12, 13, 23, 25, 28, 30, 31], "150": [4, 8], "152": 16, "153760": [], "156": 16, "157": [], "158": [], "159": 16, "15g": 6, "15pm": 28, "16": [1, 2, 3, 4, 5, 8, 9, 10, 25, 28, 30], "160": 16, "1603": 3, "161": 16, "162": 16, "16231451": 4, "163": 16, "16384": 3, "164": 16, "167": 16, "17": [1, 2, 8, 25], "172": 16, "173": 16, "176": 16, "178": 16, "179": 16, "1797": 1, "18": [2, 6, 7, 8, 9, 10, 25, 28], "1807": 4, "181036": [], "18392847": [], "18c1c4": [], "19": [2, 25, 28], "1940": [], "1943": 12, "19569961": 29, "19680801": [], "1970": [22, 28], "1973": 9, "1979": 6, "1_1": 12, "1_2": 12, "1_3": 12, "1cm": [0, 8, 10, 25, 28], "1d": [1, 2, 3], "1e": [2, 4, 13, 14, 31], "1e10": 14, "1e1e1": [], "1e4": 6, "1f": 1, "1k": 22, "1n": [0, 28], "1x": [0, 28], "2": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 25, 27, 31], "20": [0, 1, 2, 6, 7, 8, 16, 17, 25, 26, 28, 29, 30, 31], "200": [0, 2, 3, 4, 8, 9, 10], "2000": [0, 29], "2001": [], "2004": [13, 30], "2006": 27, "2007": [], "20072279": [], "2008": [28, 31], "2009": [], "2010": 1, "2011": [1, 31], "2012": 31, "2013": [], "2014": [4, 31], "2015": 1, "2016": [0, 28], "2018": [0, 6, 29], "2020": [], "2021": [6, 14, 29, 31], "2022": 28, "2024": [], "2025": [18, 28, 29, 30, 31], "21": [0, 1, 5, 7, 9, 12, 22, 28, 29, 30], "2116753732": 4, "215pm": [26, 28], "2167072": [], "22": [0, 1, 5, 12, 13, 22, 28, 29, 30], "221": 8, "225": 4, "22948497": [], "23": [1, 12, 22], "24": [0, 1, 22, 28], "242424": [], "24292f": [], "25": [2, 3, 4, 5, 6, 8, 9, 11, 29], "250": [2, 4, 7, 9], "25000": [], "250154": [], "252124": [], "253775": [], "255": 3, "256": [4, 31], "25x": 23, "26": [], "26303845": [], "264": [], "265": [], "265109911": 4, "266": [], "269": [], "27": 1, "270": [], "278": [30, 31], "27n_": 25, "28": [1, 3, 4], "283": [30, 31], "2830637392": 4, "2861": 25, "2873": 9, "2882": 25, "2886": 25, "2890": [0, 28], "2892": 25, "29": 29, "2915": 25, "2931": 28, "29364655": [], "294399745619595": [], "296247": [], "2968": 28, "2980": 28, "298273": [], "298375": [], "2990": 28, "2_": 12, "2_1": 12, "2_2": 12, "2_3": 12, "2_i": 12, "2_m": [6, 25], "2_t": 13, "2_x": 25, "2a": 17, "2a1968": [], "2b": 25, "2b2b2b": [], "2c8f433990d1": 31, "2cm": 8, "2d": [1, 3, 11, 12, 21, 28], "2e": 6, "2f": [0, 7, 9, 10, 11, 12, 28], "2g": 2, "2g_i": 2, "2k": 3, "2m": 6, "2mvizaqfst8": 29, "2n": [0, 2, 3, 28, 29], "2nd": 9, "2p": 25, "2pt": 4, "2x": [0, 3, 8, 13, 28], "2x_ix_jy_iy_j": 8, "2x_j": 8, "2y_i": 10, "2y_j": 8, "3": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 24, 25, 26, 28, 30, 31], "30": [0, 1, 4, 6, 7, 10, 13, 26, 31], "30000": [0, 28], "3072": 3, "31": [12, 22, 25], "315": [6, 29, 31], "3155": [0, 5, 6, 29, 30, 31], "32": [3, 4, 6, 12, 13, 22, 25, 31], "3200": 1, "3250": 1, "3297": [], "33": [12, 22, 26], "3303": [], "3310": [], "332331": [], "333": 7, "3331": [], "3337": [], "34": 22, "3436": [0, 28], "3437": [0, 28], "35": [0, 6, 23, 28, 30, 31], "3581341341": 4, "359": [5, 30], "36": [0, 5, 6, 18, 23, 25], "37": [23, 30], "370782966": 4, "38": [23, 25], "39": [0, 26, 28], "3d": [2, 3, 4, 6, 13, 16], "3d73a9": [], "3f": [1, 3, 9], "3n": 22, "3x": [2, 8], "3x_i": 2, "3y": 8, "4": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 23, 25, 28, 30, 31], "40": [1, 6, 26, 28], "400": 4, "4000": 28, "40008b9a5380fcacce3976bf7c08af5b": 31, "4050": [27, 28], "41": 22, "4155": [2, 15], "41589548": [], "42": [1, 4, 8, 9, 10, 22], "43": [0, 7, 22], "4310": 28, "436462435": 4, "437a6b": [], "44": [0, 22, 30, 31], "45": [26, 28], "46": [26, 28], "462": 7, "47": [26, 28], "473d18": [], "479465113": 4, "47958494": [], "48": [], "48257387": [26, 28], "49": [5, 6, 11], "49152": 3, "4940954": [0, 28], "4990": 25, "4992": 25, "4997": 25, "4c4b4be8": [], "4c4c7f": [9, 10], "4d": 3, "4f": 6, "4pm": [26, 28], "4y": 8, "4y_i": 10, "5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 22, 23, 25, 28, 29, 30, 31], "50": [1, 2, 3, 4, 6, 7, 8, 10, 13, 28, 29, 31], "500": [1, 3, 4, 6, 9, 10, 13, 31], "5018": 25, "506": [], "507d50": [9, 10], "50j": 13, "50x10": 1, "51": 10, "510": 1, "512132": [], "515151": [], "5177783846": 4, "53": 9, "5391cf": [], "54": [6, 25], "5411205": [], "54894451": [], "55": 1, "56": 1, "56536": [0, 28], "569": 1, "57": [0, 8, 26, 28], "571": [5, 30], "58": [10, 26, 28], "58a6ff70": [], "591317992": 4, "5ca7e4": [], "5cm": 25, "5f": [8, 31], "5x": [8, 18], "5y": 8, "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 18, 22, 25, 26, 28, 29, 30, 31], "60": [1, 3], "60000": 4, "6019067271": 4, "606439": [], "622cbc": [], "625": 7, "63": 1, "64": [1, 3, 4, 13, 22, 28, 31], "64x50": 1, "65": [1, 8, 9], "66666691": [], "66707b": [], "66ccee": [], "66e9ec": [], "6730c5": [], "6887363571": 4, "69": [16, 25], "69069n_": 25, "691": [], "6980": 31, "6e7681": [], "6e7781": [], "6f98b3": [], "6n_": 25, "7": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 22, 23, 25, 27, 28, 29, 31], "70": [1, 7], "702c00": [], "70653767": 4, "71": 1, "724": 3, "72f088": [], "73": [], "7304881": [], "737373": [], "75": [5, 6, 8, 11], "76": [26, 28], "765": 7, "77": [26, 28], "7718": 9, "7782028952": 4, "77893972": [], "78": [], "797979": [], "7998f2": [], "79c0ff": [], "7d7d58": [9, 10], "7ee787": [], "7f4707": [], "8": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 22, 25, 26, 28, 30], "80": [0, 1, 5, 8, 17, 29], "800": [4, 7], "8045e5": [], "81": 1, "815am": [26, 28], "81b19b": [], "8250df": [], "85": 1, "8702784034": 4, "8786ac": [], "88": 28, "8a4600": [], "8b949e": [], "8c8c8c": [], "8f": 6, "8g": 6, "8n": 22, "8x8": 1, "9": [0, 1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 22, 25, 28, 31], "90": 1, "9040": 9, "91": [26, 28], "912583": [], "91cbff": [], "92": [26, 28], "93": 16, "931": [0, 28], "933": [5, 30], "937": 25, "938": 25, "939": [0, 25, 28], "94": 25, "95": [1, 11], "953800": [], "954": 25, "955820c21e8b": 4, "96": 6, "960": 25, "961": 25, "962": 25, "9649652536": 4, "96611194e": [], "974eb7": [], "9780387310732": 27, "9780387848570": 27, "9781098134174": 28, "9781492032632": 27, "9781801819312": 28, "97898392": 29, "98": [0, 1, 16], "985": 25, "986": 25, "98661b": [], "989": 25, "9898ff": [9, 10], "99": [13, 16, 31], "991": 25, "992": 25, "993": 25, "996": 5, "996b00": [], "999": [9, 25, 31], "9e86c8": [], "9e8741": [], "9f4e55": [], "9x": 6, "9y": 6, "A": [2, 3, 5, 6, 7, 10, 11, 12, 13, 15, 16, 19, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31], "AND": 2, "AS": [], "AT": [], "And": [0, 3, 4, 5, 6, 9, 13, 20, 21, 23, 25, 30], "As": [0, 1, 2, 3, 4, 5, 6, 8, 10, 12, 13, 15, 16, 22, 23, 25, 28, 29, 30, 31], "At": [0, 4, 6, 13, 20, 28, 31], "BE": [0, 28], "BUT": [], "BY": [], "Be": [2, 18, 21, 28], "Being": 13, "But": [0, 1, 2, 3, 5, 6, 9, 10, 16, 25, 29], "By": [0, 3, 5, 6, 12, 13, 17, 19, 22, 28, 29, 30, 31], "FOR": [], "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30, 31], "IF": [6, 29, 31], "IN": 27, "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 18, 21, 22, 23, 25, 28, 29, 30, 31], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30, 31], "Ising": [5, 12, 29, 30], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 20, 21, 22, 23, 25, 28, 29, 30, 31], "Its": [1, 2, 4, 11], "NO": [], "NOT": [], "No": [6, 9, 28, 29, 31], "Not": [0, 1, 5, 6, 29, 30, 31], "OF": [], "ON": [], "OR": 25, "Of": 25, "On": [0, 3, 23, 25, 26, 27, 28, 31], "One": [0, 1, 3, 4, 5, 6, 7, 8, 11, 12, 13, 17, 25, 29, 30, 31], "Or": [0, 1, 6, 28], "SUCH": [], "Such": [0, 6, 12, 16, 25, 31], "THE": [], "TO": [], "That": [0, 5, 7, 10, 11, 12, 14, 23, 25, 28], "The": [4, 10, 13, 14, 16, 17, 18, 19, 20, 22, 23, 24, 25, 26, 27], "Then": [0, 1, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 22, 28, 30, 31], "There": [0, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 22, 23, 25, 26, 28, 29, 30, 31], "These": [0, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 17, 18, 22, 23, 25, 26, 28, 29, 30, 31], "To": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 22, 25, 29, 30, 31], "WITH": [], "With": [0, 5, 6, 8, 9, 10, 11, 12, 14, 16, 19, 22, 23, 25, 28, 29], "_": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 22, 23, 28, 29, 30, 31], "_0": [5, 8, 10, 11, 13, 29, 30], "_1": [2, 5, 6, 8, 10, 11, 12, 13, 14, 22, 29, 30, 31], "_2": [2, 5, 8, 11, 12, 13, 22, 29, 31], "_3": 22, "_4": 22, "_9": [13, 31], "__class__": 10, "__doc__": 6, "__future__": [8, 9], "__import__": [], "__init__": 1, "__main__": 2, "__name__": [2, 10], "__path__": [], "_auto1": [2, 3, 4, 5, 6, 7, 12, 13, 22, 25, 29, 30], "_auto10": [6, 12], "_auto11": 6, "_auto12": 6, "_auto2": [2, 3, 4, 5, 6, 12, 13, 22, 25], "_auto3": [3, 4, 5, 6, 12, 13, 22], "_auto4": [4, 6, 12, 13, 22], "_auto5": [4, 6, 12, 13, 22], "_auto6": [4, 6, 12, 22], "_auto7": [4, 6, 12, 22], "_auto8": [6, 12], "_auto9": [6, 12], "_build": [0, 21, 23, 27, 28], "_c": 1, "_center": [], "_compile_transl": [], "_compon": 11, "_depth": 9, "_export": [15, 16, 19], "_fraction": 9, "_i": [0, 1, 2, 5, 6, 7, 8, 11, 12, 13, 19, 23, 28, 29, 30, 31], "_j": [0, 1, 2, 3, 5, 6, 8, 13, 19, 23, 29, 30, 31], "_k": [13, 30, 31], "_l": 12, "_lambda": 6, "_leaf": 9, "_m": 10, "_multilayer_perceptron": [], "_n": [2, 5, 8, 11, 13, 29, 30, 31], "_node": 9, "_norm": [], "_p": [5, 8, 29, 30], "_parse_numpydoc_see_also_sect": [], "_pydevd_bundl": [], "_ratio": 11, "_sampl": 9, "_split": [6, 9, 23], "_t": [13, 31], "_test": [6, 23], "_varianc": 11, "_weight": 9, "a0": 3, "a0111f": [], "a0faa0": [9, 10], "a1": [0, 28], "a11": [], "a12236": [], "a2": [0, 28], "a25e53": [], "a2bffc": [], "a3": [0, 28], "a4": [0, 28], "a5d6ff": [], "a_": [0, 1, 16, 22, 28, 29], "a_0": [0, 28], "a_1a": [0, 28], "a_2a": [0, 28], "a_3": [0, 28], "a_3a": [0, 28], "a_4": [0, 28], "a_4a": [0, 28], "a_h": 1, "a_i": [0, 1, 2, 12, 28], "a_j": [1, 12], "a_k": [0, 1, 12], "aa": [], "aaa": [], "aaron": 27, "ab": [0, 2, 5, 13, 14, 28, 29, 31], "ab6369": [], "ab_channel": 21, "abandon": 1, "abe338": [], "abid": 25, "abil": [0, 10], "abl": [0, 1, 4, 5, 6, 7, 10, 12, 13, 16, 18, 19, 20, 23, 29, 30, 31], "about": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 19, 20, 21, 22, 23, 26, 31], "abov": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 25, 27, 28, 29, 31], "abovement": [6, 23, 28], "abscissa": [13, 30], "absent": 31, "absolut": [0, 2, 5, 6, 13, 28, 29, 30], "absorb": [29, 30], "abstract": [1, 31], "abund": 31, "acceler": [13, 31], "accept": [0, 3, 6, 9, 23, 29, 31], "access": [3, 11, 25, 28, 31], "accid": [4, 6], "accompani": [0, 28, 29], "accomplish": [8, 9, 13, 31], "accord": [0, 1, 2, 5, 6, 9, 12, 13, 14, 25, 28, 30, 31], "accordingli": 11, "account": [0, 3, 5, 13, 15, 16, 20, 25, 28, 31], "accumul": [12, 13, 25, 31], "accur": [0, 3, 4, 6, 10, 13, 31], "accuraci": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 28, 29, 30], "accuracy_scor": [0, 1, 10, 28], "accuracy_score_numpi": 1, "achiev": [0, 1, 5, 6, 8, 12, 22, 28, 31], "aco": 25, "acquaint": 21, "acquir": [1, 21, 28], "acr": [], "across": [1, 3, 6, 9, 17, 21, 28], "act": [1, 3, 22, 31], "action": 25, "activ": [0, 2, 3, 4, 9, 15, 24, 26, 28, 31], "activest": [], "actual": [0, 1, 4, 5, 6, 8, 11, 15, 16, 18, 22, 25, 28, 29, 30, 31], "ad": [1, 3, 4, 5, 8, 13, 15, 16, 22, 30, 31], "ada_clf": 10, "adaboostclassifi": 10, "adadelta": [13, 31], "adagrad": 23, "adam": [1, 3, 4, 23, 28], "adapt": [4, 6, 13, 17, 27, 30], "add": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 15, 16, 17, 18, 20, 25, 26, 28, 29, 30, 31], "add6ff": [], "add_": [], "add_subplot": [1, 7, 12, 14], "addendum": 5, "addeventlisten": [], "addit": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 15, 21, 22, 23, 25, 26, 27, 28, 29], "addition": [12, 13, 30, 31], "address": [1, 9, 11, 13, 28, 31], "adjac": [3, 12], "adjoint": [5, 29], "adjust": [0, 5, 12, 13, 30, 31], "admir": [0, 28], "advanc": [4, 6, 12, 27, 28, 31], "advantag": [1, 3, 5, 6, 10, 13, 19, 22, 30, 31], "adversari": 28, "advis": [], "afecionado": 28, "affect": [3, 15, 19], "affin": [0, 3, 8, 11, 29], "afford": 3, "aficionado": 28, "aforement": 14, "african": [], "after": [0, 1, 2, 4, 5, 6, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "afterward": [0, 28], "ag": [0, 7, 28, 29], "ag_0": 2, "again": [0, 1, 4, 5, 6, 7, 8, 10, 11, 12, 13, 23, 25, 28, 29, 30], "against": [1, 4, 7, 10], "agegroup": 7, "agegroupmean": 7, "aggreg": [9, 10, 31], "agorithm": 10, "agre": [5, 6, 25, 29, 30, 31], "agreement": [13, 31], "ahead": 9, "ai": [0, 27], "aid": [11, 20, 31], "aim": [0, 1, 4, 6, 7, 11, 14, 16, 17, 19, 20, 21, 22, 23, 29], "ainv": 5, "airplan": 3, "aka": 5, "al": [0, 2, 4, 16, 17, 20, 27, 28, 29, 30], "alarm": [5, 7], "aldo": 29, "algebra": [0, 3, 5, 13, 21, 29, 30], "algorithm": [0, 1, 2, 4, 5, 6, 7, 8, 13, 14, 16, 21, 22, 23, 25, 27], "align": [0, 2, 5, 6, 7, 8, 13, 25, 28, 29, 30], "all": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], "allevi": [1, 13, 30], "alloc": [3, 22], "allow": [0, 1, 2, 3, 5, 6, 8, 10, 13, 15, 21, 22, 23, 28, 29, 30, 31], "almost": [0, 1, 6, 8, 11, 13, 25, 30, 31], "alon": [2, 9, 31], "along": [2, 3, 4, 5, 6, 9, 10, 11, 15, 20, 21, 22, 28, 29, 30], "alpha": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 14, 25, 28, 29, 30, 31], "alpha_": [10, 31], "alpha_0": 3, "alpha_1": 3, "alpha_2": 3, "alpha_i": [3, 13], "alpha_k": 13, "alpha_m": 10, "alpha_n": 3, "alpha_opt": 13, "alreadi": [2, 3, 4, 5, 6, 10, 12, 15, 21, 22, 25, 28, 29, 30], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "alter": 1, "altern": [0, 1, 4, 5, 6, 8, 9, 11, 13, 15, 18, 22, 23, 28, 29, 31], "although": [0, 1, 5, 6, 8, 10, 13, 16, 19, 20, 28, 31], "alwai": [0, 3, 5, 6, 12, 13, 16, 19, 23, 25, 28, 29, 30, 31], "am": 4, "ame2016": [0, 28], "american": [], "amjith": [], "among": [0, 3, 5, 9, 10, 12, 22, 28, 29], "amongst": 5, "amount": [0, 1, 3, 4, 6, 8, 10, 14, 21], "an": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 25, 26, 27, 29, 30, 31], "an_": 25, "anaconda": [0, 1, 21, 23, 28], "analogi": 13, "analys": 6, "analysi": [1, 3, 4, 7, 14, 19, 22, 27, 31], "analyt": [2, 3, 5, 6, 7, 12, 13, 17, 21, 23, 28, 29, 30, 31], "analyz": [0, 1, 3, 4, 5, 6, 16, 23, 25, 29, 30, 31], "andrew": 1, "angl": [0, 3, 9, 29, 31], "anharmon": 3, "ani": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 19, 25, 28, 29, 31], "anim": [4, 12], "ann": 12, "annot": [0, 1, 3, 7, 8, 28], "announc": 28, "anonym": 18, "anoth": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 22, 23, 25, 28, 29, 31], "ansatz": [0, 18, 28], "answer": [0, 1, 3, 5, 6, 19, 22, 23, 26, 28], "antialias": [2, 6], "anticip": 4, "anymor": [1, 8], "anyon": [4, 8, 15], "anyth": [1, 15, 16, 25], "anytim": [26, 28], "apach": 1, "apart": [11, 13, 30, 31], "api": [1, 21, 28], "appar": 2, "appear": [0, 1, 3, 13, 22, 25], "append": [1, 3, 4, 8, 9, 13, 19, 28, 31], "appendix": 23, "appli": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 18, 23, 25, 27, 28, 29, 31], "applic": [0, 1, 3, 4, 5, 6, 7, 9, 12, 13, 16, 22, 25, 27, 28, 29, 30, 31], "apply_gradi": 4, "approach": [1, 2, 4, 5, 6, 9, 10, 11, 12, 13, 15, 16, 18, 21, 23, 25, 27, 29, 30], "approch": 23, "appropri": [2, 6, 9, 12, 13, 17, 21, 25, 31], "approv": 28, "approx": [0, 2, 3, 6, 10, 11, 13, 18, 23, 25, 28, 30, 31], "approxim": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 13, 19, 23, 25, 28, 29, 30, 31], "apt": [0, 21, 23, 28], "aq": 25, "ar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31], "aragorn": 28, "arang": [1, 3, 4, 6, 7, 9, 10, 12, 13, 28, 31], "arbitrari": [1, 4, 6, 8, 12, 13, 25, 30], "arbitrarili": [0, 1, 11, 28, 31], "arc": 6, "architectur": [3, 4, 12], "archiv": 23, "area": [0, 3, 6, 27, 28], "argmax": [1, 11], "argmin": [4, 10, 14], "argsort": 11, "argu": [1, 13], "arguement": 19, "argument": [0, 2, 3, 5, 11, 12, 13, 17, 28, 29, 31], "aris": [0, 6, 12, 13, 25, 28, 30], "arithmet": [0, 13, 22, 28], "arm": [6, 29, 31], "armadillo": 22, "armin": [], "around": [0, 1, 4, 5, 6, 11, 18, 23, 25, 28], "arrai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 16, 18, 21, 23, 25, 29, 30, 31], "arrang": [3, 28], "arraybox": 13, "arriv": [0, 6, 9, 11, 22, 25, 28], "arrow": 12, "arrowprop": 8, "art": [0, 1, 21], "articl": [0, 3, 4, 6, 10, 19, 28, 29, 30, 31], "artifici": [0, 2, 7, 12, 27, 28], "artificialneuron": 12, "arug": 13, "arxiv": [3, 4, 31], "asarrai": [0, 6, 9, 29, 31], "asid": 29, "ask": [5, 6, 11, 12, 15, 19, 23], "aspect": [0, 6, 21, 28, 29], "assembl": 3, "assembli": [0, 28], "assert": 4, "assess": [0, 6, 23, 28, 29], "asset": [], "assici": 4, "assign": [0, 7, 8, 9, 12, 13, 14, 15, 24, 26, 27, 28], "associ": [0, 6, 9, 12, 14, 25, 28], "assum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 22, 23, 25, 28, 29, 30, 31], "assumpt": [0, 3, 5, 6, 9, 11, 25, 28, 29], "ast": [0, 5, 6, 28], "astyp": [4, 9, 10], "asymmetri": [0, 28], "asymptot": [4, 6, 31], "atom": [0, 28], "attain": 31, "attempt": [0, 4, 6, 7, 8, 10, 28, 29, 31], "attend": 28, "attent": [0, 22, 28], "attract": [0, 10, 28], "attribut": [0, 9, 28], "audi": [0, 28], "audio": [3, 4], "august": [28, 29], "aurelien": [0, 27, 28], "austfjel": 6, "auth": 15, "authent": 15, "author": [0, 1, 10, 25], "authour": 28, "auto": [9, 10, 25], "auto_exampl": [23, 29], "autocor": 25, "autocorrelation_tim": 25, "autocorrelform": 25, "autocovari": 25, "autoencod": [4, 21, 28], "autoencond": 21, "autograd": [21, 28], "autom": [0, 21, 27, 28], "automac": 22, "automag": 28, "automat": [0, 1, 2, 3, 4, 11, 16, 21, 22, 28], "automobil": 3, "autonom": 4, "avail": [0, 1, 4, 6, 10, 11, 20, 21, 22, 23, 24, 26, 27, 28], "averag": [0, 1, 3, 6, 9, 10, 13, 14, 25, 26, 28, 29], "avoid": [0, 4, 5, 6, 9, 11, 13, 18, 22, 29, 31], "awai": [2, 3, 6, 29, 31], "awar": [2, 10], "award": [26, 28], "ax": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22, 23, 28], "axes3d": [2, 6, 13, 30, 31], "axes_grid1": 6, "axhlin": 8, "axi": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 22, 25, 28, 29, 30, 31], "axiom": 5, "axvlin": [4, 8], "axvspan": 4, "b": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 14, 15, 16, 17, 19, 20, 25, 26, 28, 29, 30, 31], "b1": 8, "b19db4": [], "b1bac4": [], "b2": 8, "b3": 8, "b35900": [], "b89784": [], "b_": [0, 1, 22], "b_0": 0, "b_1": [0, 2, 12, 13, 31], "b_2": [0, 13], "b_5": [13, 31], "b_group": 9, "b_i": [0, 1, 2, 12, 28], "b_ia_": [0, 28], "b_ia_i": 0, "b_index": 9, "b_j": [1, 12], "b_k": [0, 1, 12, 13, 31], "b_m": 12, "b_score": 9, "b_valu": 9, "ba": 31, "babcock": 28, "bach": 31, "bachelor": [24, 26], "back": [0, 3, 4, 5, 6, 8, 9, 10, 15, 16, 22, 25, 28, 31], "backbon": 22, "backend": [1, 4], "background": [27, 28], "backpropag": [1, 31], "backslash": [], "backtrack": 9, "backup": 22, "backward": [1, 2, 4, 12, 22, 31], "bad": [6, 17, 29], "badli": 25, "bag": [9, 21, 28], "bag_clf": 10, "baggin": 28, "baggingboot": 10, "baggingclassifi": 10, "baggingtre": 10, "bailei": [], "balanc": [6, 31], "ballpark": 18, "band": 22, "bandwidth": 22, "banner": [], "bar": [0, 6, 11, 23, 28], "barber": 27, "bare": [4, 10], "base": [0, 1, 3, 4, 5, 7, 8, 9, 10, 14, 15, 16, 17, 21, 25, 26, 27, 28, 29, 30], "basi": [5, 7, 8, 10, 11, 12, 13, 22, 29, 30], "basic": [6, 8, 12, 13, 14, 15, 21, 23, 25, 28], "basin": 31, "batch": [3, 4, 11, 12, 13, 30], "batch_shap": 4, "batch_siz": [1, 3, 4], "batchnorm": 4, "bay": 7, "bayesian": [5, 21, 27, 28], "bbbbbb": [], "beauti": [], "becaus": [0, 1, 2, 3, 4, 5, 6, 8, 9, 12, 13, 14, 28, 29, 30, 31], "becom": [0, 1, 2, 5, 6, 7, 9, 12, 13, 19, 25, 28, 29, 30, 31], "been": [0, 1, 2, 3, 4, 5, 6, 11, 12, 13, 20, 21, 22, 23, 28, 29, 31], "befor": [0, 1, 2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 17, 18, 19, 20, 22, 23, 25, 28, 29, 31], "beforehand": [0, 25, 28], "began": [], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 22, 25, 26, 28, 29, 30, 31], "behav": [1, 6, 13, 30], "behavior": [0, 1, 13, 28, 30, 31], "behaviour": [12, 31], "behind": [0, 1, 6, 8, 13, 28, 30], "being": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12, 13, 17, 20, 25, 28, 29, 30, 31], "believ": [9, 22], "belong": [7, 8, 9, 13, 14, 30], "below": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 18, 22, 23, 25, 28, 29, 30, 31], "benchmark": 10, "benefici": [1, 13], "benefit": [0, 1, 4, 11, 13, 21, 28, 30, 31], "bengio": [1, 27, 28, 29, 31], "benign": [1, 7], "besid": [4, 5, 30], "bessel": [5, 29], "best": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 18, 26, 28, 29, 30, 31], "beta": [1, 3, 10, 11, 13, 16, 17, 19, 28, 29, 30], "beta1": [], "beta2": [], "beta_": [3, 13, 17, 29], "beta_0": [1, 3, 13, 29], "beta_1": [1, 3, 10, 13, 29, 31], "beta_1m_": 31, "beta_1x_i": 13, "beta_2": [3, 13, 31], "beta_2v_": 31, "beta_3": 3, "beta_i": [3, 31], "beta_j": [13, 29], "beta_k": 13, "beta_linreg": 13, "beta_m": 10, "beta_mg_m": 10, "beta_n": 3, "better": [0, 1, 2, 3, 4, 6, 9, 10, 11, 12, 13, 19, 20, 28, 29, 31], "between": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 23, 25, 28, 29, 30, 31], "beyond": [0, 1, 5, 6, 8, 13, 28, 29, 30, 31], "bf": [13, 14, 19, 22, 25, 30], "bf5400": [], "bg": 28, "bgd": [13, 31], "bia": [0, 1, 2, 3, 5, 8, 9, 10, 12, 13, 20, 28, 29, 30], "bias": [1, 2, 3, 5, 6, 9, 12, 19, 31], "bib": [], "bibliographi": 23, "bibtex": [], "big": [0, 1, 2, 5, 6, 14, 19, 31], "bigger": [1, 6, 29], "bigr": 12, "bike": 9, "bilbo": 28, "billion": [3, 12, 21, 31], "bin": [7, 25], "binari": [0, 3, 5, 7, 9, 10, 12, 28], "binarycrossentropi": 4, "bind": 0, "binomi": [21, 25, 28], "binsboot": 6, "bioinformat": 0, "biolog": [1, 12], "bios1100": [21, 28], "bird": [0, 3], "birth": 28, "bishop": [27, 28], "bit": [1, 4, 19, 22, 25, 28], "bitwis": 25, "bivari": 2, "bk": [13, 31], "bla": [22, 28], "black": [8, 9, 14], "block": [6, 10, 21, 22, 25, 28], "blockquot": [], "blog": 28, "blogpost": 4, "blue": [0, 3], "bm": [], "bmatrix": [0, 1, 3, 5, 7, 8, 11, 13, 22, 28, 29, 30, 31], "bmi": 1, "bodi": [0, 1, 4, 12], "bold": 1, "boldfac": [0, 5, 16, 29, 30], "boldsymbol": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 23, 28, 30, 31], "boltzmann": [12, 21, 28], "book": [17, 23, 27, 28, 29], "book1": 27, "boolean": [4, 17], "boost": [1, 9, 21, 28], "boostrap": 10, "bootstrap": [1, 13, 19, 21, 23, 28, 31], "born": 31, "borrow": 28, "boston_dataset": [], "bot": 8, "both": [0, 1, 4, 5, 6, 8, 9, 10, 13, 14, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31], "bottl": 7, "bottou": 31, "bound": [8, 12, 31], "boundari": [2, 4, 8, 11, 12], "bousquet": 31, "bower": [], "box": [4, 9], "boyd": [8, 13, 30], "bracket": [4, 25], "brain": [1, 7, 12], "branch": [9, 28], "break": [0, 4, 6, 11, 14, 28, 31], "breast": [5, 7, 11], "breviti": 13, "brew": [0, 21, 23, 28], "brg": 8, "brian": [], "brief": [23, 29], "briefli": [0, 16, 19, 28], "bring": [0, 5, 6, 10, 29, 31], "britt": [26, 28], "broad": 0, "broadli": 28, "brought": [13, 21, 28], "brownle": 4, "browser": [15, 28], "brute": [3, 5, 11, 29], "bsd": [], "budget": 31, "buffer_s": 4, "bug": [], "bugfix": [], "bui": 4, "build": [0, 4, 5, 6, 10, 16, 22, 25, 28], "built": [1, 3, 4, 6], "bunch": 11, "bundl": [], "busi": [], "byte": [22, 28], "c": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 24, 25, 26, 27, 29, 30, 31], "c1": [8, 11], "c2": [8, 11], "c4a2f5": [], "c5e478": [], "c9d1d9": [], "c_": [8, 9, 10, 13, 25, 30, 31], "c_0": 25, "c_1": 12, "c_2": 12, "c_3": 12, "c_4": 12, "c_i": [12, 13, 31], "c_k": 25, "ca": [1, 28], "caab6d": [], "cach": 10, "cal": [0, 8, 10, 12, 13, 30, 31], "calcul": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 19, 22, 25, 28, 31], "california": 23, "call": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31], "calor": [0, 29], "caltech": [], "cambridg": [13, 27, 30], "can": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 29, 30], "cancel": [0, 13, 28, 29], "cancer": [5, 10], "cancerpd": 7, "candid": [8, 9, 10, 31], "cannot": [0, 1, 4, 5, 6, 7, 8, 9, 23, 25, 29, 30, 31], "canopi": [0, 21, 23, 28], "canva": [15, 16, 19, 20, 23, 28], "cap": 5, "capabl": [0, 1, 8, 13, 21, 28], "capac": [2, 26], "capita": [], "caption": [20, 23], "captur": [4, 11, 12, 28], "car": [3, 4], "card": [0, 7, 28], "cardin": 1, "care": [11, 15, 19, 31], "carefulli": [13, 31], "carlo": [0, 6, 21, 25, 27, 28], "carri": [2, 6, 7, 23], "cart": 10, "case": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 16, 21, 22, 23, 28], "casella": 27, "cast": 1, "cat": [3, 4], "catch": 0, "categor": [0, 1, 3, 9, 11, 28], "categori": [0, 1, 3, 7, 10, 12, 14, 28], "categorical_crossentropi": [1, 3], "caus": [0, 5, 6, 25, 28, 29, 30, 31], "causal": 0, "causat": [0, 28], "cax": 1, "cb": [6, 28], "cbar": 1, "cc": [0, 1, 5, 13, 28, 29, 30, 31], "cc398b": [], "ccbb44": [], "ccc": [5, 12, 30], "cdf": 25, "cdot": [0, 2, 6, 12, 13, 14, 22, 25, 28, 30, 31], "celebr": [13, 30], "cell": 4, "center": [0, 1, 6, 7, 8, 9, 11, 14, 18, 23, 25, 28, 29, 31], "central": [0, 3, 5, 6, 8, 16, 20, 22, 28, 29], "centroid": [14, 25], "centroid_differ": 14, "centuri": 3, "certain": [0, 3, 6, 7, 9, 25, 28, 29], "cf222e": [], "cffi": [], "cg": 13, "cha": [], "chain": [0, 1, 13, 21, 25, 28], "challeng": 15, "chanc": [1, 5, 13, 25, 31], "chang": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 19, 22, 23, 25, 28, 29, 30, 31], "changelog": [], "channel": 3, "chapter": [0, 6, 10, 11, 16, 17, 19, 22, 23, 27, 28, 29, 30, 31], "chapter3": [0, 23], "charact": [0, 3, 5, 28, 29, 30], "character": [8, 9, 10, 12, 25], "characterist": [0, 1, 3, 10, 13, 28], "charg": [0, 28], "charl": [], "charset": [], "chase": 4, "chatgpt": [15, 23], "chd": 7, "chddata": 7, "cheap": [5, 29, 30, 31], "cheaper": [1, 13, 31], "check": [1, 3, 4, 5, 11, 13, 15, 16, 19, 22, 28, 31], "checkmark": 3, "checkpoint": 4, "checkpoint_dir": 4, "checkpoint_prefix": 4, "chen": 10, "cheng": 29, "chiaramont": 2, "childcar": 16, "children": 16, "choic": [0, 1, 2, 3, 4, 6, 9, 12, 13, 14, 20, 22, 28, 29, 30, 31], "choleski": [5, 22, 29, 30], "choos": [2, 3, 6, 9, 10, 11, 13, 14, 15, 18, 19, 23, 30], "chosen": [0, 1, 2, 6, 8, 9, 10, 13, 16, 25, 28, 30, 31], "chosen_datapoint": 1, "christian": 27, "christoph": [27, 28], "chunk": 31, "cifar": 3, "cifar10": 3, "circ": [1, 12, 31], "circl": [0, 8, 12, 29, 31], "circuit": 3, "circumfer": 9, "circumv": [1, 5, 13, 29, 30, 31], "citat": [], "cite": [20, 23], "ckpt": 4, "claim": [], "clariti": 25, "class": [0, 1, 3, 4, 6, 7, 8, 9, 11, 12, 13, 25, 28], "class_nam": [3, 9], "class_val": 9, "class_valu": 9, "classic": [7, 9, 13], "classif": [0, 3, 5, 6, 7, 8, 11, 12, 21, 23, 27, 28, 29], "classifi": [0, 1, 4, 7, 9, 10, 11, 28], "classificaton": 1, "classifii": 10, "claus": [], "clean": 1, "clear": [1, 5, 10, 12, 13, 31], "clearli": [0, 3, 5, 6, 7, 8, 25, 29, 30], "clever": [1, 10], "clf": [0, 6, 8, 9, 10, 28, 29], "clf3": 0, "clf_lasso": 6, "clf_ridg": 6, "cli": 15, "click": [], "clip": [3, 25, 31], "clock": 31, "clone": [15, 26], "close": [0, 1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 18, 25, 27, 28, 30, 31], "closer": [3, 5, 13, 29, 30, 31], "closest": [8, 11, 13, 14], "closur": [21, 28], "cloud": [21, 28], "cluster": [0, 1, 4, 6, 11, 21, 28], "cluster_label": 14, "cm": [1, 2, 3, 6, 8, 13, 30, 31], "cmap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 28], "cmap_arg": 6, "cmd": [9, 15], "cn_": 25, "cnn": 12, "cnn_kera": 3, "cntk": [21, 28], "co": [0, 2, 3, 6, 9, 13, 28], "code": [0, 3, 4, 6, 7, 8, 18, 19, 21, 22, 25, 27], "codec": [], "coef": [0, 28], "coef0": 8, "coef_": [0, 5, 6, 8, 9, 13, 16, 28, 29, 30, 31], "coeff": 5, "coeffici": [0, 3, 5, 6, 7, 8, 9, 13, 18, 22, 28, 29, 31], "coerc": [0, 6, 28], "coin": [10, 25], "coin_toss": 10, "col": [0, 11, 28, 29], "colab": [21, 28], "cold": 9, "colinear": [], "collabor": [20, 23], "collaps": 8, "collect": [2, 6, 10, 11, 17, 21, 25, 27, 28], "collinear": [5, 29, 30], "color": [0, 3, 4, 6, 8, 9, 10, 25, 31], "color_channel": 3, "color_cod": 6, "colorbar": [1, 6, 20], "colsample_bytre": 10, "colsaobject": 10, "column": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12, 16, 17, 18, 19, 22, 28, 29, 30, 31], "columntransform": 9, "com": [4, 6, 15, 16, 19, 20, 21, 23, 27, 28, 30, 31], "combin": [1, 2, 5, 6, 7, 10, 15, 18, 25], "come": [0, 1, 3, 4, 5, 12, 13, 14, 15, 28, 29, 30, 31], "comfort": [], "command": [0, 1, 15], "comment": [0, 4, 5, 6, 20, 23], "commerci": [0, 21, 23, 28], "commit": 15, "commod": [0, 28], "common": [0, 1, 3, 5, 6, 7, 9, 11, 13, 14, 16, 23, 25, 28, 29, 30, 31], "commonli": [0, 1, 4, 6, 7, 9, 13, 14, 29, 31], "commonmark": [], "commun": [0, 12, 15, 23], "commut": 3, "commutatitav": 3, "compact": [0, 1, 3, 5, 6, 7, 9, 11, 12, 13, 14, 28, 29], "compair": 0, "compar": [0, 3, 4, 5, 6, 11, 13, 18, 22, 23, 28, 29, 30, 31], "comparison": [2, 4, 13], "compat": 7, "compens": 31, "compet": 0, "competit": 10, "compil": [0, 1, 3, 4, 13, 21, 22, 28], "complet": [0, 2, 3, 4, 9, 12, 15, 16, 17, 18, 19, 20, 28], "completenn": 12, "complex": [1, 5, 8, 9, 11, 12, 13, 16, 19, 28, 30, 31], "complianc": [], "complic": [0, 1, 9, 13, 23, 28, 30, 31], "compoment": 29, "compon": [0, 1, 3, 4, 5, 6, 7, 9, 14, 16, 21, 28, 29, 30], "components_": 11, "compos": [9, 12, 13, 14, 21, 28], "compphys": [0, 6, 16, 20, 21, 23, 24, 26, 27, 28, 29, 30], "compress": [0, 28, 29], "compris": 6, "compromis": [5, 29, 30], "compulsori": [21, 28], "comput": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 17, 18, 21, 22, 23, 24, 25, 27, 28, 29, 30], "computation": [0, 3, 6, 9, 13, 25, 28, 30, 31], "computationalscienceuio": 28, "computerlab": 23, "concaten": [2, 4, 6, 14], "concav": [1, 13, 29, 30], "concentr": 10, "concept": [0, 2, 21, 28, 29], "conceptu": [12, 13, 30], "concern": [0, 1, 4, 7, 28, 30], "concic": 28, "conclud": [0, 5, 13, 31], "conclus": 1, "cond": 2, "conda": [0, 1, 21, 23, 28], "condis": 29, "condit": [0, 2, 4, 5, 6, 8, 9, 11, 13, 25, 28, 29, 31], "conduct": 21, "condwav": 2, "confid": [0, 5, 6, 7, 8, 19, 28, 29], "configur": 3, "confirm": [5, 12], "conform": [], "confus": [5, 6, 7, 10, 22, 29], "confusion_matrix": 9, "congruenti": 25, "conjug": [4, 8], "conjugaci": 13, "conjunct": 3, "connect": [0, 1, 3, 4, 9, 11, 12, 13, 22, 28, 29, 30], "consensu": 31, "consequ": [5, 6, 8, 10, 12, 13, 29, 30, 31], "consequenti": [], "conserv": [5, 14, 29, 30], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 16, 19, 22, 23, 25, 28, 29, 30, 31], "consider": [0, 1, 5, 13, 28, 29, 30], "consist": [1, 2, 3, 4, 6, 12, 13, 23, 25, 29, 30], "consol": [], "const": [], "constant": [0, 2, 4, 5, 6, 8, 12, 13, 16, 18, 25, 28, 29, 30, 31], "constitu": [0, 28], "constitut": [2, 6], "constrain": [1, 3, 5, 7, 11, 30], "constraint": [5, 6, 8, 13, 29, 30], "construct": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 22, 25, 28, 29], "constructor": [], "consum": 31, "contact": [0, 28], "contain": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 18, 19, 22, 23, 25, 27, 28, 29, 30, 31], "contemporari": 28, "content": [1, 15, 20, 21, 22, 28, 30, 31], "context": [6, 10, 13, 23, 30, 31], "contigu": 22, "contin": 19, "continu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 19, 22, 23, 25, 28, 29, 30, 31], "contour": [9, 10, 13], "contourf": [8, 9, 10], "contract": [], "contrast": [1, 4, 9, 10, 12, 28, 31], "contribut": [0, 3, 5, 13, 18, 25, 28, 29, 30, 31], "contributor": [0, 23], "control": [0, 1, 3, 9, 13, 15, 21, 28], "conv": [3, 4], "conv2d": [3, 4], "conv2dtranspos": 4, "convei": 28, "conveni": [5, 6, 12, 13, 22, 23, 28, 30, 31], "convent": [12, 29], "converg": [1, 2, 4, 5, 8, 13, 14, 18, 29, 30], "convergencewarn": [], "convers": [20, 31], "convert": [0, 1, 4, 5, 9, 11, 13, 22, 28, 29, 30], "converttomatrix": 4, "convex": [4, 5, 7, 29], "convinc": [13, 30], "convolut": [1, 4, 21, 28], "cool": [4, 9], "coolwarm": 6, "coordin": [5, 12, 14, 29, 30, 31], "coorel": [], "copi": [0, 1, 14, 15, 29], "copyright": [], "core": 10, "corel": 28, "coronari": 7, "corr": [5, 7, 11, 29], "correalt": [11, 21], "correct": [0, 1, 2, 3, 4, 5, 7, 13, 15, 19, 20, 22, 25, 28, 29, 30], "correctli": [1, 2, 6, 7, 10, 18, 19, 23], "correl": [0, 1, 3, 5, 6, 7, 10, 12, 13, 21, 25, 28, 30, 31], "correlation_matrix": [5, 7, 11, 29], "correspond": [0, 3, 5, 6, 8, 9, 11, 12, 21, 22, 23, 25, 28, 29, 30], "cortex": 12, "cosin": [3, 6], "cost": [0, 2, 3, 5, 6, 7, 8, 9, 12, 13, 16, 17, 18, 19, 23, 28], "cost_deep_grad": 2, "cost_funct": 2, "cost_function_deep": 2, "cost_function_deep_grad": 2, "cost_function_grad": 2, "cost_grad": 2, "cost_histori": [], "cost_ol": [], "cost_ridg": [], "cost_sum": 2, "costli": 31, "costol": [13, 31], "could": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 22, 23, 25, 28, 29, 30, 31], "coulomb": [0, 28], "count": [0, 9, 15, 24, 25, 26, 28], "counteract": 31, "counterpart": 28, "countor": 13, "coupl": [4, 5, 6], "cours": [0, 1, 3, 5, 11, 15, 16, 17, 19, 20, 23, 26, 29], "coursework": 15, "courvil": [27, 28, 29, 31], "cov": [5, 6, 11, 22, 25, 28, 29], "cov_xi": [5, 11, 29], "cov_xx": [5, 11, 29], "cov_yi": [5, 11, 29], "covari": [0, 7, 21, 22, 28, 30], "covariance_matrix": [5, 11, 14], "cover": [0, 5, 21, 26, 27, 29, 30], "covert": [0, 28], "covxi": 25, "covxx": 25, "covxz": 25, "covyi": 25, "covyz": 25, "covzz": 25, "cpu": 1, "craft": 3, "crash": 31, "creat": [1, 3, 4, 5, 9, 10, 11, 12, 15, 18, 19, 21, 28, 31], "create_biases_and_weight": 1, "create_convolutional_neural_network_kera": 3, "create_neural_network_kera": 1, "create_x": [5, 11], "credit": [0, 7, 26, 28], "crim": [], "crime": [], "criteria": [0, 4, 9, 10, 14, 25, 28], "criterion": [9, 10, 13, 18, 30, 31], "critic": [6, 23, 29], "critiqu": 23, "cross": [0, 1, 3, 7, 9, 10, 13, 15, 21, 25, 28, 29, 30, 31], "cross_entropi": 4, "cross_val_scor": 6, "cross_valid": [7, 10], "crossvalid": 6, "crucial": [1, 25, 31], "cs231": 3, "csr_matrix": [22, 28], "css": [], "csv": [0, 4, 6, 7, 9], "ctnk": 1, "cubic": 0, "cumbersom": 5, "cumsum": [10, 11, 28], "cumul": [7, 10, 25, 31], "cumulative_heads_ratio": 10, "cup": 5, "current": [1, 2, 3, 4, 13, 14, 15, 16, 27, 30, 31], "curs": [0, 29], "curv": [6, 7, 10, 12, 23], "curvatur": [13, 30, 31], "custom": [6, 14], "custom_cmap": [9, 10], "custom_cmap2": [9, 10], "custom_lin": [], "cutpoint": 9, "cv": [6, 7, 10], "cvxbook": [13, 30], "cvxopt": [5, 8, 29], "cycl": [1, 12], "cycler": [], "d": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20, 22, 25, 26, 28, 29, 30, 31], "d166a3": [], "d2_g_t": 2, "d2a8ff": [], "d4d0ab": [], "d71835": [], "d9dee3": [], "d_f": [13, 30], "d_g_t": 2, "d_net_out": 2, "da": 3, "dagger": [5, 22, 29, 30], "dai": [1, 9, 21], "damag": [], "damp": 3, "darget": 9, "darkr": 25, "dat": [0, 28], "dat_id": [0, 6, 7, 9, 28], "data": [2, 4, 5, 8, 10, 12, 13, 14, 16, 19, 20, 22, 23, 27, 30, 31], "data1": 14, "data2": 14, "data3": 14, "data4": 14, "data_id": [0, 6, 7, 9, 28], "data_indic": 1, "data_panda": 28, "data_path": [0, 6, 7, 9, 28], "databas": 1, "datafil": [0, 6, 7, 9, 28], "datafram": [0, 4, 5, 7, 9, 11, 28, 29], "datapoint": [1, 5, 6, 7, 11, 13, 16, 30, 31], "datasci": [15, 16, 19], "dataset": [0, 4, 6, 7, 8, 9, 10, 11, 13, 14, 16, 23, 28, 30, 31], "datatyp": 4, "date": [15, 18, 23, 28, 29, 30, 31], "daughter": 10, "davi": [], "david": 27, "dbb7ff": [], "dbh": 1, "dbo": 1, "dcc6e0": [], "dcomposit": 22, "ddot": 2, "de": 31, "dead": 1, "deadlin": [15, 20], "deal": [0, 1, 3, 5, 6, 8, 11, 13, 14, 19, 22, 25, 28, 29, 30, 31], "dealt": 0, "debt": 7, "debug": [0, 5, 6, 29, 30, 31], "debugg": [], "decad": [0, 3, 31], "decai": [0, 13, 25, 28], "decemb": [26, 28], "decent": 10, "decid": [0, 2, 3, 5, 6, 9, 18, 29, 30, 31], "decim": [0, 28], "decis": [0, 1, 8, 11, 21, 27, 28], "decision_funct": 8, "decision_tre": 9, "decisiontreeclassifi": [9, 10], "decisiontreeregressor": [0, 9, 10], "declar": [0, 4, 20, 22, 28], "declare_namespac": [], "decompos": [5, 6, 22, 29, 30], "decomposit": [0, 6, 12, 28], "decompost": [5, 29, 30], "deconvolut": 3, "decorrel": [10, 13, 31], "decreas": [1, 2, 4, 5, 6, 10, 11, 13, 19, 30, 31], "dedic": 20, "deduc": [0, 28], "deep": [3, 7, 12, 13, 21, 27, 29, 30], "deep_neural_network": 2, "deep_param": 2, "deep_tree_clf": [9, 10], "deep_tree_clf1": 9, "deep_tree_clf2": 9, "deepen": [5, 21, 28], "deeper": [0, 3, 4, 28], "deeplearningbook": [27, 28, 30, 31], "deer": 3, "def": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 25, 28, 29, 30, 31], "def_covari": 25, "default": [0, 1, 2, 4, 6, 7, 22, 28, 29], "default_tim": 4, "defect": [5, 29, 30], "defici": [5, 29, 30], "defin": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 22, 23, 25, 29, 30, 31], "definit": [1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 22, 25, 29, 30, 31], "defint": 25, "degre": [3, 5, 6, 8, 9, 10, 11, 15, 16, 19, 20, 23, 25, 28, 30, 31], "deisenroth": 29, "del": 1, "delet": [6, 15], "delimit": 4, "deliv": [15, 24, 28], "delta": [0, 2, 3, 6, 8, 12, 13, 14, 28, 31], "delta_": [1, 22], "delta_0": 3, "delta_1": 3, "delta_2": 3, "delta_3": 3, "delta_4": 3, "delta_5": 3, "delta_h": [0, 1, 28], "delta_j": [3, 12], "delta_k": 12, "delta_l": [1, 3], "delta_momentum": [13, 31], "delta_n": [0, 3, 28], "delug": 21, "delv": 0, "demand": [13, 30], "demonstr": [0, 3, 5, 6, 7, 11, 12, 19, 21, 28, 29, 30, 31], "den": 4, "denomin": [1, 5, 31], "denot": [1, 2, 6, 7, 13, 25, 30, 31], "dens": [1, 3, 4], "densiti": [0, 2, 6, 25], "depart": [26, 28, 29, 30, 31], "depend": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 21, 22, 23, 25, 28, 29, 30, 31], "depict": 25, "deploy": [0, 21, 23, 28], "depth": [0, 3, 9, 10, 22], "der": [], "deriv": [0, 1, 2, 6, 7, 8, 10, 11, 13, 18, 21, 23, 28], "derivati": 13, "derivative_fn": 13, "descend": [5, 9, 11, 29, 30], "descent": [0, 1, 3, 7, 8, 12, 28, 29], "describ": [0, 2, 4, 5, 6, 8, 10, 11, 12, 13, 19, 20, 22, 23, 28, 31], "descript": [0, 8, 9, 20, 23, 28], "design": [0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 17, 18, 23, 28, 30, 31], "designmatrix": [0, 28], "desir": [0, 2, 4, 5, 13, 14, 28, 29, 30, 31], "desktop": 15, "despit": [1, 12, 31], "destroi": 22, "det": [5, 22, 29, 30], "detail": [0, 6, 11, 13, 14, 18, 22, 23, 29, 30, 31], "detect": [3, 8, 12], "determin": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 18, 22, 25, 28, 29, 30, 31], "determinist": [7, 13, 25, 30, 31], "dev": [1, 23], "develop": [0, 3, 5, 8, 10, 11, 12, 21, 22, 23, 28, 29], "deviat": [0, 1, 2, 4, 5, 6, 17, 18, 19, 23, 25, 28, 29, 31], "devis": 12, "df": [4, 8, 11, 13, 28], "df1": 28, "di": [], "diag": [5, 8, 29, 30, 31], "diagnost": [1, 10], "diagon": [0, 5, 7, 13, 18, 19, 22, 25, 28, 29, 30, 31], "diagonaliz": [5, 29, 30], "diagram": 10, "diagsvd": 6, "dice": [6, 25], "dict": [6, 8], "dictionari": [], "did": [0, 1, 5, 6, 7, 10, 11, 14, 16, 23, 28], "die": 1, "diff": 2, "diff1": 2, "diff2": 2, "diff_ag": 2, "diffeent": 8, "differ": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30], "differenti": [0, 3, 16, 21, 22, 28, 29, 30], "difficult": [0, 1, 6, 10, 13, 25, 28, 31], "difficulti": [0, 1, 13, 28, 30, 31], "diffonedim": 2, "digit": [0, 1, 3, 4, 6, 26, 28], "dilemma": [13, 31], "dilut": 1, "dim": [4, 11, 14, 22], "dimens": [0, 1, 2, 3, 4, 5, 8, 11, 14, 16, 22, 28, 29, 30], "dimension": [0, 4, 5, 6, 9, 11, 13, 14, 19, 21, 22, 23, 28, 29, 30, 31], "dimensionless": [0, 3, 28], "diment": 22, "diminish": 31, "dimnsion": 4, "diod": 3, "direct": [0, 1, 2, 4, 11, 12, 13, 14, 28, 29, 30, 31], "directli": [1, 4, 5, 6, 18, 25, 29, 30], "directori": [], "disadvantag": [0, 28, 31], "disappear": [3, 6], "disc_loss": 4, "disc_tap": 4, "discard": [6, 11, 31], "disciplin": [0, 3, 12], "disclaim": 25, "discord": 28, "discourag": [13, 15, 30], "discov": [0, 28], "discover": 5, "discret": [1, 3, 5, 7, 13], "discrimin": [4, 7, 10, 11], "discriminator_loss": 4, "discriminator_loss_list": 4, "discriminator_model": 4, "discriminator_optim": 4, "discuss": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 20, 21, 22, 23, 25, 27, 28, 29, 30, 31], "diseas": 7, "disguis": [6, 29, 31], "disk": 31, "disord": [1, 7], "displai": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 23, 25, 28, 29, 31], "displaystyl": [0, 5, 17, 28, 29, 30, 31], "disregard": [0, 28], "dissimilar": [11, 14], "dist": 14, "distanc": [8, 9, 11, 14, 25], "distance_list": 9, "distinct": [3, 7, 8, 9, 10, 14], "distinctli": 8, "distinguish": [0, 4, 7, 8, 25, 28], "distplot": [], "distribut": [0, 1, 4, 6, 7, 10, 11, 13, 14, 18, 19, 21, 22, 23, 28, 29, 30, 31], "distrubut": [0, 21, 23, 28], "div": [], "dive": [0, 8, 22, 28], "diverg": [1, 13, 30, 31], "divid": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12, 18, 19, 25, 28, 29, 31], "divis": [6, 8, 9, 13, 18, 22, 25, 31], "dl": [], "dna": 7, "dnn": [0, 1, 2, 4, 12, 28], "dnn1": 4, "dnn2_gru2": 4, "dnn_kera": 1, "dnn_model": 1, "dnn_numpi": 1, "dnn_scikit": [0, 1, 28], "do": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 22, 23, 28, 29, 30], "doc": [0, 15, 16, 19, 21, 23, 24, 26, 27, 28], "document": [4, 13, 15], "docutil": [], "doe": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 17, 18, 19, 22, 23, 25, 28, 31], "doesn": [3, 9, 12, 28, 31], "dog": [1, 3, 4], "dollar": [], "domain": [5, 8, 13, 23, 30], "domcontentload": [], "domin": [0, 28], "don": [0, 1, 3, 5, 6, 8, 11, 13, 15, 16, 21, 23, 28, 29, 31], "done": [0, 2, 3, 4, 5, 6, 9, 10, 11, 13, 16, 20, 22, 23, 28, 29, 30, 31], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 18, 22, 23, 25, 28, 29, 30, 31], "doubl": [3, 4, 16, 22, 28], "doubli": 1, "doubt": 23, "down": [0, 3, 6, 9, 11, 12, 13, 30, 31], "download": [0, 1, 3, 5, 6, 15, 20, 22, 27, 28], "downsampl": 3, "dozen": 1, "dq": 6, "draft": 20, "drag": 13, "dragon": [], "dramat": 11, "drastic": 4, "draw": [4, 6, 10, 13, 30], "drawback": [0, 1, 3, 13, 29, 30, 31], "drawn": [1, 4, 6, 7, 11, 25, 28], "drive": [3, 4], "driven": 3, "drop": [0, 1, 5, 6, 11, 13, 25, 28, 29, 30], "dropna": [0, 6, 28], "dropout": 4, "dt": [2, 3, 13, 25], "dtype": [0, 1, 3, 4, 14, 22, 28], "dub": [0, 28], "due": [1, 2, 5, 6, 8, 10, 12, 13, 18, 26, 28, 29, 30, 31], "dummi": [], "dure": [0, 1, 3, 4, 8, 9, 11, 20, 21, 23, 28, 31], "dwell": [], "dwh": 1, "dwo": 1, "dx": [2, 3, 8, 25], "dx_1": 25, "dx_1p": 6, "dx_2p": 6, "dx_mp": 6, "dx_n": 25, "dxp": 6, "dy": [1, 8, 25], "dynam": 4, "dz": 8, "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 26, 28, 29, 30, 31], "e1e1e1": [], "e_": [0, 2, 28], "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 22, 24, 25, 26, 28, 29, 30, 31], "eapprox": [0, 28], "earli": [1, 13, 31], "earlier": [0, 5, 7, 8, 9, 11, 12, 13, 20, 28, 29], "earthexplor": 6, "eas": [6, 9, 14], "easi": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 21, 22, 28, 29, 30, 31], "easier": [5, 6, 8, 9, 13, 15, 20, 23, 25, 28, 29, 30], "easiest": [13, 18], "easili": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 28, 29, 30, 31], "eastern": [26, 28], "ebind": [0, 28], "eblock": 9, "ec8e2c": [], "econometr": 28, "economi": 5, "ecosystem": [21, 28], "ect": 24, "edg": 3, "edgecolor": 6, "edit": [], "editor": [15, 20], "edu": [13, 23, 30], "educ": [0, 23, 28], "ee6677": [], "eff": 25, "effect": [1, 4, 10, 13, 16, 17, 18, 25, 31], "effic": 1, "effici": [0, 3, 10, 13, 21, 22, 25, 28, 31], "effort": 19, "efron": 6, "egrad": 13, "eig": [5, 11, 13, 22, 25, 28, 29, 30, 31], "eigen": 25, "eigenpair": [5, 11, 29, 30], "eigenvalu": [0, 5, 8, 11, 13, 22, 28, 29, 30, 31], "eigenvector": [5, 11, 13, 29, 30], "eight": [22, 28], "eigval": [22, 25, 28], "eigvalu": [11, 13, 30, 31], "eigvec": [22, 25, 28], "eigvector": [11, 13, 30, 31], "eir": [26, 28], "eispack": [22, 28], "either": [1, 5, 6, 7, 8, 9, 10, 11, 13, 18, 19, 23, 25, 28, 29, 30, 31], "eivind": 26, "eivinsto": 26, "ekstr\u00f8m": 4, "elabor": 25, "elarn": 3, "electr": [0, 3, 12, 28], "electron": 28, "eleg": 11, "element": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 19, 20, 21, 22, 23, 27, 29, 31], "elementari": [10, 13, 22], "elementwis": [3, 13], "elementwise_grad": [2, 13], "elessar": 28, "elif": 14, "elim": 22, "elimin": [3, 8], "elin": [26, 28], "ell_": [], "ellipsi": 16, "els": [1, 3, 4, 7, 9, 12, 13, 16, 22], "elu": 1, "elus": [0, 28], "em": [], "email": [24, 26, 28], "emb": [], "embed": [0, 11, 29], "embodi": [6, 23], "emit": 25, "emner": 27, "emph": 31, "emphas": [0, 10, 21, 28], "emphasi": [0, 21, 27, 28], "empir": [1, 11, 25], "emploi": [0, 1, 5, 6, 11, 13, 25, 28, 29, 30], "employ": 0, "empti": [6, 10, 15], "emul": 12, "en": [21, 23, 27], "enabl": [11, 31], "enbodi": 6, "encod": [0, 3, 5, 9, 11, 14, 28, 29, 30], "encompass": [0, 23, 25], "encount": [0, 1, 5, 7, 13, 15, 23, 25, 28, 29, 30, 31], "encourag": [15, 23], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22, 25, 26, 28, 29, 30, 31], "endblock": [], "endfor": [], "endif": [], "endors": [], "endpoint": [3, 6], "energi": [0, 4, 6], "enforc": 12, "eng": 27, "engin": [0, 1, 3, 4, 21, 28], "english": 23, "enjoi": 31, "enocurag": 23, "enorm": 3, "enough": [0, 6, 13, 28, 30, 31], "ensembl": [1, 9, 28], "ensur": [0, 1, 2, 3, 5, 6, 11, 13, 18, 25, 29, 30, 31], "entail": 28, "enter": [5, 6, 29, 30, 31], "enthought": [0, 21, 23, 28], "entir": [1, 3, 7, 9, 21, 25, 28, 31], "entireti": [], "entiti": [9, 12, 22, 28], "entri": [0, 5, 8, 11, 12, 22, 28, 29, 31], "entropi": [1, 3, 7, 10, 13, 28, 30, 31], "enumer": [0, 1, 2, 3, 4, 6, 8, 28, 29, 31], "env": 25, "environ": [2, 21, 23, 28], "environemnt": 15, "eo": [0, 6], "eol": 0, "eosfit": 0, "epoch": [0, 1, 3, 4, 12, 13, 28, 31], "eppstein": [], "epsilon": [0, 5, 6, 7, 13, 23, 28, 29, 30, 31], "epsilon_": [0, 28], "epsilon_0": [0, 28], "epsilon_1": [0, 28], "epsilon_2": [0, 28], "epsilon_i": [0, 28, 29], "eq": [3, 13, 14, 22, 25, 30], "eqnarrai": [3, 5, 6], "equal": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 16, 18, 22, 23, 25, 28, 29, 30, 31], "equat": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 17, 19, 22, 25, 28, 31], "equilibrium": [2, 12], "equiv": [3, 13, 22, 25, 30, 31], "equival": [0, 1, 5, 7, 8, 11, 13, 21, 22, 28, 29, 30, 31], "equivel": 19, "erf": 25, "eriador": 28, "eric": [], "err": [0, 10], "err_": 6, "err_sqr": 2, "errat": [13, 30, 31], "erron": 2, "error": [1, 2, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 18, 19, 21, 22, 23, 25, 31], "error_estimate_corr_tim": 25, "error_hidden": 1, "error_output": 1, "escap": [13, 30, 31], "escapehtml": [], "especi": [1, 3, 9, 12, 13, 15, 18, 23, 31], "essenti": [0, 5, 6, 9, 10, 12, 14, 15, 23, 25, 29, 30, 31], "establish": [0, 6, 10, 11, 16, 23], "estim": [0, 1, 5, 6, 7, 10, 11, 13, 19, 21, 25, 28, 29, 30, 31], "estimated_mse_fold": 6, "estimated_mse_kfold": 6, "estimated_mse_sklearn": 6, "et": [0, 2, 4, 16, 17, 20, 27, 28, 29, 30], "eta": [0, 1, 3, 8, 12, 13, 18, 28, 30, 31], "eta0": [8, 13], "eta_": 13, "eta_j": 31, "eta_t": [13, 31], "eta_v": [0, 1, 3, 28], "etc": [0, 1, 3, 5, 7, 8, 9, 11, 12, 13, 14, 21, 22, 23, 25, 29, 30, 31], "ethic": 21, "euclidean": [0, 14, 29, 31], "euler": [], "evalu": [0, 2, 3, 4, 5, 6, 9, 13, 15, 16, 17, 19, 23, 25, 28, 29, 30, 31], "evalut": [13, 23], "even": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 21, 22, 25, 28, 29, 30, 31], "evenli": 4, "event": [5, 7, 10, 25], "eventu": [0, 5, 6, 11, 12, 13, 23, 26, 29, 30, 31], "everi": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15, 21, 25, 26, 28, 29, 30, 31], "everyth": [4, 12, 16, 18], "everywher": [4, 13, 30], "evolv": 0, "exact": [0, 5, 11, 12, 13, 22, 25, 28, 29, 31], "exactli": [0, 3, 4, 6, 12, 18, 21, 29, 31], "exam": 28, "examin": 6, "exampl": [0, 5, 11, 12, 13, 15, 16, 18, 20, 21, 22, 23, 25, 27], "exce": [1, 12, 13, 31], "exceed": 31, "excel": [0, 1, 4, 5, 10, 20, 23, 28, 29], "except": [3, 4, 6, 8, 9, 22], "excess": [0, 28], "exchang": 31, "excit": 0, "exclud": [1, 6, 12, 29, 31], "exclus": [0, 1, 3, 6, 25, 28], "execut": [2, 5, 13, 15, 29, 30, 31], "exemplari": [], "exemplifi": [13, 31], "exercic": [26, 28], "exercis": [5, 21, 23, 24, 26, 28, 30, 31], "exhaust": [6, 31], "exhibit": [0, 5, 6, 8, 28, 29], "exist": [0, 1, 2, 3, 5, 6, 7, 8, 9, 13, 19, 22, 23, 28, 30, 31], "exit": [5, 22, 29, 30], "exp": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 25, 29, 30, 31], "exp_term": 1, "expand": [5, 7, 11, 13, 30], "expans": [0, 3, 5, 8, 10, 12, 13, 28, 29, 30], "expect": [0, 1, 5, 6, 7, 11, 12, 13, 15, 18, 21, 23, 28, 29, 31], "expectation_value_of_h_wrt_p": 25, "expens": [6, 10, 13, 16, 30, 31], "experi": [0, 1, 6, 8, 13, 15, 21, 23, 28, 29, 30, 31], "experiment": [0, 4, 6, 9, 25, 28], "expert": [1, 9], "explain": [0, 6, 9, 10, 11, 13, 16, 19, 23, 28, 30], "explained_variance_ratio_": 11, "explan": [], "explanatori": [0, 28], "explicit": [0, 3, 6, 13, 22, 23, 28, 29, 30, 31], "explicitli": [0, 4], "explod": 1, "exploit": [0, 3, 12, 13, 28, 31], "explor": [1, 4, 6, 8, 13, 18, 21, 23, 28, 30, 31], "expon": 1, "exponenti": [0, 1, 5, 6, 10, 13, 25, 28, 30], "export": [9, 15, 16, 19, 20], "export_graphviz": 9, "export_text": 9, "exporttext": 9, "expos": 21, "express": [0, 2, 3, 5, 6, 7, 10, 12, 13, 18, 22, 23, 25, 28, 30, 31], "exptmean": 25, "exptvari": 25, "extend": [0, 2, 7, 11, 13, 21, 28, 31], "extend_path": [], "extens": [0, 12, 15, 21, 28], "extent": [0, 1, 6, 27], "extern": [3, 6, 9], "extra": [1, 3, 5, 15, 26, 28, 29, 30], "extract": [0, 3, 5, 6, 7, 8, 11, 13, 16, 17, 22, 28, 29], "extrapol": [0, 28], "extrem": [0, 1, 4, 5, 6, 7, 8, 9, 13, 15, 16, 22, 29, 30, 31], "extremum": [13, 30], "extrins": 11, "ey": [0, 5, 6, 13, 14, 18, 22, 28, 29, 30, 31], "f": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 19, 22, 25, 26, 28, 29, 30, 31], "f1": 13, "f11": [0, 28], "f12": [0, 28], "f13": [0, 28], "f1_grad": 13, "f1d": 13, "f2": 13, "f26196": [], "f2_grad_x1": 13, "f2_grad_x1_analyt": 13, "f2_grad_x2": 13, "f2_grad_x2_analyt": 13, "f2f2f2": [], "f3": 13, "f3_grad": 13, "f3_grad_analyt": 13, "f4": 13, "f4_grad": 13, "f4_grad_analyt": 13, "f5": 13, "f5_grad": 13, "f5a394": [], "f5ab35": [], "f5f5f5": [], "f6": 13, "f6_for": 13, "f6_for_grad": 13, "f6_grad_analyt": 13, "f6_while": 13, "f6_while_grad": 13, "f7": 13, "f78c6c": [], "f7_grad": 13, "f7_grad_analyt": 13, "f8": 13, "f8_grad": 13, "f8f8f2": [], "f9": [0, 13, 28], "f9_altern": 13, "f9_alternative_grad": 13, "f9_grad": 13, "f_": 10, "f_0": [3, 10], "f_1": [10, 13, 30], "f_2": [12, 13, 30], "f_3": 12, "f_d": 25, "f_grad": 13, "f_grad_analyt": 13, "f_i": [0, 6, 12, 16], "f_m": [3, 10], "f_n": 3, "f_vec": 2, "face": [13, 28, 30], "facecolor": [6, 8, 25], "facil": [0, 21], "facilit": 12, "fact": [0, 1, 3, 5, 9, 11, 12, 13, 28, 29, 30, 31], "facto": 31, "factor": [0, 1, 3, 5, 6, 9, 10, 11, 13, 22, 25, 28, 29, 30], "factori": 13, "fad000": [], "fade": 6, "fae4c2": [], "fafab0": [9, 10], "fail": [0, 6, 13, 26, 28, 30], "failur": 7, "fairli": [1, 2, 18, 25, 31], "faisal": [16, 29], "fake": 4, "fake_loss": 4, "fake_output": 4, "fall": [8, 9, 24], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 14, 16, 17, 22, 28, 29, 30, 31], "famili": [0, 7, 8, 25, 29, 31], "familiar": [0, 3, 5, 6, 8, 15, 21, 22, 23, 25, 28], "famou": [6, 12], "far": [0, 3, 4, 5, 6, 8, 11, 12, 13, 14, 16, 20, 28, 29, 30, 31], "fashion": [0, 9, 10, 28, 31], "fast": [1, 3, 6, 10, 12, 13, 21, 25, 28, 30, 31], "faster": [1, 11, 13, 31], "fastest": [13, 22, 30], "fatal": [], "favor": [7, 31], "favorit": 25, "fc": 3, "fcfcfc": [], "fdac54": [], "fdf2e2": [], "featur": [0, 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 15, 17, 18, 19, 21, 25, 28, 30, 31], "feature_nam": [1, 7, 9], "feautur": 9, "fed": 1, "feed": [0, 2, 3, 11, 21, 28], "feed_forward": 1, "feed_forward_out": 1, "feed_forward_train": 1, "feedback": [4, 20, 28], "feeddorward": 4, "feedforward": [1, 4, 12], "feel": [0, 5, 6, 11, 13, 15, 16, 18, 21, 23, 26, 28], "feet": [], "fefef": [], "fefeff": [], "felt": 23, "fenc": [], "fernando": [], "fetch": [6, 15], "few": [1, 3, 4, 5, 9, 17, 18, 19, 25, 28], "fewer": [0, 9, 11, 19, 28, 31], "ff7b72": [], "ff9492": [], "ffa07a": [], "ffa657": [], "ffb757": [], "ffd700": [], "ffd900": [], "ffd9002e": [], "ffffff": [], "ffnn": [1, 12], "fi": [], "field": [0, 3, 6, 12, 19, 21], "fifth": [0, 6, 28], "fig": [0, 1, 2, 3, 4, 6, 7, 12, 13, 14, 23, 28], "fig_id": [0, 6, 7, 9, 28], "figaxi": 25, "figsiz": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 28], "figur": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 21, 23, 28, 29, 30, 31], "figure_id": [0, 6, 7, 9, 28], "figurefil": [0, 6, 7, 9, 28], "file": [0, 4, 5, 6, 7, 9, 15, 20, 23, 28], "file_prefix": 4, "filenam": 28, "fill": [5, 9, 18, 29, 30], "filter": [3, 4], "final": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 20, 23, 24, 25, 26, 28, 30], "financ": 0, "find": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 21, 23, 25, 28, 29, 30, 31], "fine": [0, 14], "finish": [2, 20], "finit": [3, 5, 6, 12, 13, 17, 25, 29, 30], "finnicki": 15, "first": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 19, 22, 23, 25, 26, 27, 29, 31], "first_moment": 31, "first_term": 31, "firsteigvector": 11, "fit": [1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 17, 18, 19, 23, 25, 29, 31], "fit_beta": 29, "fit_intercept": [0, 5, 6, 16, 29, 30, 31], "fit_mod": 9, "fit_theta": [6, 31], "fit_transform": [0, 6, 8, 9, 11, 15, 19], "fiti": [0, 28], "five": [0, 9, 28, 29], "fix": [0, 3, 4, 6, 10, 11, 12, 13, 23, 28], "flag": 4, "flat": [12, 13, 30, 31], "flatten": [1, 3, 4, 5, 22], "flavor": [], "flexibl": [1, 6, 8, 10, 12, 28, 31], "flip": [26, 28], "float": [0, 3, 4, 5, 9, 11, 13, 14, 22, 28, 29, 30], "float32": [4, 9], "float64": [4, 22, 28], "flop": [5, 22, 29, 30], "flow": [1, 4, 12], "fluctuat": [5, 31], "fly": 11, "fm": 0, "fmax": 3, "fmesh": 13, "fn": 7, "focu": [0, 3, 4, 5, 6, 15, 21, 23, 27, 28, 29, 30, 31], "focus": [1, 6, 7, 22, 29, 31], "fold": [6, 9, 23], "folder": [0, 4, 6, 15, 20, 23, 28], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31], "font": [7, 20, 25, 28], "fontdict": 25, "fontsiz": [1, 6, 8, 9, 10, 25], "fontweight": 1, "footprint": [3, 31], "foral": [8, 29], "forc": [0, 5, 6, 10, 11, 29, 30, 31], "forcast": 4, "forcier": [], "forecast": [4, 12], "forest": [0, 1, 9, 21, 28], "forget": [11, 31], "form": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 21, 22, 23, 25, 28, 29, 30, 31], "formal": [3, 4, 14, 18, 25], "format": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 20, 21, 25, 27], "format_data": 4, "formatstrformatt": [6, 13, 30, 31], "formatt": [], "formul": [4, 6, 11, 14], "formula": [3, 13, 25, 30], "forth": [4, 12], "fortran": [0, 21, 22, 28], "fortran2003": [21, 28], "fortran2008": 23, "fortran90": 25, "fortun": [0, 11, 29], "forward": [0, 3, 6, 21, 22, 28, 31], "found": [1, 2, 4, 5, 6, 12, 13, 19, 20, 23, 28, 29, 31], "foundat": [21, 28], "four": [4, 5, 6, 8, 12, 22, 24, 26, 28, 30], "fourier": [0, 28], "fourierdef1": 3, "fourierdef2": 3, "fourierseriessign": 3, "fourth": [12, 28, 29], "fp": 7, "frac": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 22, 23, 25, 28, 29, 30, 31], "fraction": 9, "frame": [7, 31], "framework": [1, 8, 10, 25], "frank": [5, 11], "frankefunct": [5, 6, 11], "fredli": [26, 28], "free": [0, 6, 11, 13, 15, 16, 18, 21, 22, 23, 25, 26, 27, 28], "freecodecamp": 21, "freedom": [5, 30], "freeli": [0, 23], "freez": 15, "frequenc": [3, 6, 7, 25], "frequent": [0, 8, 9, 13, 30], "frequentist": 21, "fresh": 10, "fridai": [15, 26, 28], "friedman": [6, 19, 23, 27, 28], "friendli": 4, "fro": 23, "frodo": 28, "frog": 3, "from": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27], "from_cod": 9, "from_logit": [3, 4], "from_tensor_slic": 4, "front": [0, 4, 5, 28, 29, 30], "frustrat": 15, "fulfil": [2, 5, 12, 29, 30], "full": [1, 3, 5, 7, 9, 10, 13, 25, 28, 29, 30], "full_matric": [5, 29, 30], "fulli": [3, 6, 12, 25], "fullnam": [], "fun": [21, 28], "func": 2, "function": [2, 3, 4, 5, 9, 14, 15, 16, 17, 18, 19, 20, 21, 22], "functionali": 11, "fundament": [0, 6, 21, 28], "funtion": 2, "furnish": [], "further": [2, 7, 9, 19, 28], "furthermor": [0, 3, 5, 6, 7, 11, 12, 13, 21, 23, 28, 29, 30, 31], "futur": [0, 4, 8, 9, 28], "fy": [15, 23, 24, 26, 27, 28], "fys4155": 23, "fys5419": [27, 28], "fys5429": [27, 28], "f\u00f8470": [26, 28], "g": [0, 1, 2, 3, 4, 6, 8, 9, 10, 11, 13, 15, 18, 19, 25, 28, 29, 30, 31], "g0": 2, "g_": [2, 9, 10, 31], "g_0": 2, "g_1": [2, 10], "g_2": [2, 10], "g_analyt": 2, "g_dnn_ag": 2, "g_euler": 2, "g_i": 2, "g_m": [3, 10], "g_n": 3, "g_re": 2, "g_t": [2, 31], "g_t_d2t": 2, "g_t_d2x": 2, "g_t_dt": 2, "g_t_hessian": 2, "g_t_hessian_func": 2, "g_t_jacobian": 2, "g_t_jacobian_func": 2, "g_trial": 2, "g_trial_deep": 2, "g_vec": 2, "gain": [1, 5, 7, 9, 10, 13, 29, 30], "galleri": [0, 28], "game": 4, "gamge": 28, "gamma": [0, 2, 8, 9, 10, 11, 13, 28, 30], "gamma1": 8, "gamma2": 8, "gamma_": [0, 28], "gamma_0": 10, "gamma_1": 10, "gamma_1x": 10, "gamma_i": [0, 8, 25, 28], "gamma_j": 13, "gamma_k": [13, 30], "gamma_m": 10, "gamma_x": [0, 28], "gap": [8, 31], "gate": [4, 12], "gather": [0, 1, 12, 29], "gaug": 12, "gaussbacksub": 22, "gaussian": [4, 5, 6, 8, 14, 18, 25, 28], "gaussian_point": 14, "gaussian_rbf": 8, "gave": [13, 31], "gavra": 28, "gbc": 28, "gca": [2, 6, 8, 13], "gd": [1, 30], "gd_clf": 10, "gdclassiffiercgain": 10, "gdclassiffierconfus": 10, "gdclassiffierroc": 10, "gdm": 13, "gdregress": 10, "ge": [1, 5, 7, 25, 29, 30], "gen_loss": 4, "gen_tap": 4, "gender": [0, 28], "genener": 4, "gener": [0, 1, 2, 3, 5, 6, 8, 10, 11, 12, 13, 14, 15, 16, 18, 20, 22, 23, 25, 27, 29, 30, 31], "generaliz": 16, "generallay": 12, "generate_and_save_imag": 4, "generate_imag": 4, "generate_latent_point": 4, "generate_simple_clustering_dataset": 14, "generated_imag": 4, "generator_loss": 4, "generator_loss_list": 4, "generator_model": 4, "generator_optim": 4, "genom": 21, "geodes": 11, "geoff": 31, "geometr": [0, 13, 28, 31], "geometri": 5, "georg": 27, "geotif": 6, "geq": [2, 5, 8, 9, 13, 29, 30, 31], "geron": [0, 27, 28], "get": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 15, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31], "get_dummi": 9, "get_paramet": 2, "get_split": 9, "get_yaxi": 8, "get_yticklabel": 6, "gh": 15, "giant": 31, "gibb": [21, 28], "gif": 4, "gini": 10, "gini_index": 9, "ginvers": 13, "git": [0, 15, 21, 28], "gitcdn": [], "giter": [13, 31], "github": [0, 20, 21, 23, 24, 26, 27, 28, 29], "gitignor": 15, "gitlab": [0, 15, 21, 23, 28], "give": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 21, 23, 25, 28, 29, 30, 31], "given": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 22, 25, 28, 29, 30, 31], "global": [6, 7, 13, 30, 31], "glorot": 1, "gmail": [], "gnew": 13, "go": [0, 1, 3, 5, 6, 8, 9, 11, 12, 13, 15, 16, 18, 28, 29, 30], "goal": [0, 7, 9, 28], "goe": [0, 1, 2, 5, 6, 13, 14, 15, 19, 22, 28, 29, 30, 31], "goessner": [], "golden": 13, "gone": [5, 29, 30], "gong": 1, "good": [1, 3, 4, 5, 6, 9, 10, 11, 13, 15, 18, 21, 25, 27, 29, 30, 31], "goodfellow": [4, 27, 28, 29, 30], "googl": [1, 4, 21, 28], "got": [1, 6, 23], "gotten": 28, "gov": 6, "govern": 28, "gp": 27, "gpu": [1, 13, 21, 28, 31], "grad": [2, 13, 31], "grad_analyt": 13, "grad_ol": 18, "grad_ridg": 18, "grade": [23, 24], "gradient": [0, 3, 4, 7, 8, 9, 12, 21, 28, 29], "gradient_desc": 31, "gradientboostingclassifi": 10, "gradientboostingregressor": 10, "gradients_of_discrimin": 4, "gradients_of_gener": 4, "gradienttap": 4, "gradual": [1, 14], "grai": [4, 6], "granger": [], "grant": [], "graph": [1, 9, 11, 12, 13, 16, 20, 30, 31], "graph_from_dot_data": 9, "graphic": [0, 1, 9, 15, 28], "grasp": 0, "gray_r": [1, 3], "grayscal": 3, "great": [5, 13, 15, 30, 31], "greater": [1, 7, 25, 29], "greatli": 13, "greedi": 9, "green": [0, 3, 9, 25], "grei": 4, "grid": [1, 3, 6, 7, 8, 12, 25, 29, 31], "grossli": [13, 30], "ground": [0, 28], "group": [0, 6, 7, 9, 14, 15, 20, 21, 23, 24, 26, 28], "groupbi": [0, 28], "grow": [1, 3, 9, 10, 31], "growth": [0, 28], "gru": 4, "guarante": [0, 4, 13, 25, 28, 29, 30, 31], "guess": [1, 4, 10, 13, 14, 30, 31], "guestrin": 10, "gui": 15, "guid": 1, "guidelin": 20, "g\u00f6ssner": [], "h": [0, 1, 5, 6, 8, 13, 15, 19, 25, 26, 27, 28, 29, 30, 31], "h1": 2, "h_": [0, 13, 28, 30, 31], "h_0": 31, "h_1": [2, 13, 30], "h_2": [2, 13, 30], "h_m": 10, "h_t": 31, "ha": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 22, 23, 25, 28, 29, 30, 31], "haanen": [26, 28], "habit": [0, 29], "had": [0, 1, 6, 7, 13, 28, 30, 31], "hadamard": [1, 12, 13, 31], "half": [1, 8, 9], "halv": 10, "hand": [0, 1, 2, 3, 5, 11, 12, 13, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31], "handi": [3, 23], "handl": [0, 1, 2, 5, 9, 11, 15, 18, 21, 29, 30, 31], "handle_unknown": 9, "handsid": 12, "handwrit": 12, "handwritten": [1, 5], "happen": [1, 2, 3, 4, 5, 6, 10, 13, 25, 29, 30, 31], "hard": [1, 7, 8, 10, 13, 30, 31], "hardcopi": [21, 28], "harder": [0, 1, 19, 29], "harmon": 3, "hash": 31, "hasn": [], "hassl": [0, 21, 28], "hast": [21, 28], "hasti": [0, 6, 16, 17, 19, 20, 23, 27, 28, 29], "hat": [0, 1, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 18, 19, 22, 29, 30, 31], "hauser": [], "have": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31], "have_sys_un_h": [], "haven": 1, "he": 7, "head": [4, 10, 25], "header": [0, 28], "heads_proba": 10, "health": [0, 29], "hear": [0, 13, 28, 31], "heart": [0, 7, 28], "heatmap": [0, 1, 3, 7, 17, 20, 28], "heavi": 31, "heavili": 0, "heavisid": 1, "height": [1, 3, 6, 29], "held": [13, 31], "help": [0, 1, 4, 12, 13, 15, 16, 23, 28, 31], "helper": [4, 14], "henc": [0, 5, 6, 8, 9, 10, 12, 13, 28, 29, 30, 31], "henrik": [26, 28], "her": 7, "here": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "hereaft": [0, 8, 12, 28], "herebi": [], "hermitian": 22, "hessenberg": 22, "hessian": [0, 2, 5, 13], "heterogen": [9, 10], "hex": [], "hi": 7, "hidden": [1, 3, 4, 12], "hidden_bia": 1, "hidden_bias_gradi": 1, "hidden_layer_s": [0, 1, 28], "hidden_neuron": 4, "hidden_weight": 1, "hidden_weights_gradi": 1, "hierarch": [5, 29, 30], "high": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 13, 14, 21, 22, 23, 28, 29, 30, 31], "higher": [0, 1, 3, 5, 6, 8, 13, 18, 23, 28, 29, 30, 31], "highest": [1, 2], "highli": [0, 3, 4, 10, 19, 21, 22, 27, 28, 29, 30, 31], "highlight": [], "highwai": [], "hing": 8, "hint": [13, 15, 16, 29, 30], "hinton": 31, "hip": 21, "hire": 0, "hist": [4, 6, 7, 25], "histogram": [6, 7, 25], "histor": [7, 11], "histori": [3, 4, 12, 15, 31], "hitherto": 5, "hjorth": [26, 28, 29, 30, 31], "hobbi": 25, "hoc": [5, 29, 30], "hoff": 27, "hold": [1, 3, 6, 13, 14, 30, 31], "holder": [0, 28], "holdgraf_evidence_2014": [], "home": [], "homepag": [23, 28], "homework": [6, 13, 30, 31], "homogen": [1, 3, 9, 10, 13, 31], "honchar": 2, "hopefulli": [0, 11, 15, 19, 25, 28, 31], "horizont": 11, "horlyk": [26, 28], "hors": [3, 7, 28], "hot": [1, 9], "hour": [1, 21, 24, 25, 26, 28, 31], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 25, 28, 29, 30, 31], "href": [], "hspace": [0, 4, 8, 10, 25, 28], "hstack": 1, "htf": 28, "html": [0, 16, 20, 21, 23, 24, 26, 27, 28, 29, 30, 31], "http": [0, 3, 4, 6, 13, 15, 16, 19, 20, 21, 22, 23, 24, 26, 27, 28, 29, 30, 31], "huang": [0, 28], "huber": [0, 28], "huge": [1, 3, 4, 21, 31], "human": [0, 1, 3, 6, 9, 12, 29], "humid": 9, "hundr": 1, "hungri": 1, "hybrid": 24, "hydrogen": [0, 28], "hyperbol": [1, 4, 12], "hyperparam": 8, "hyperparamet": [3, 4, 5, 6, 9, 13, 18, 23, 29, 30, 31], "hyperplan": 11, "h\u00f8rlyk": [26, 28], "i": [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31], "i0": [0, 28], "i1": [0, 6, 8, 12, 28, 29, 31], "i2": [0, 8, 12, 28], "i3": [0, 12, 28], "i5": [0, 28], "i_": [13, 30, 31], "i_1": [5, 6], "i_2": [5, 6], "i_t": 31, "ian": 27, "ic": [1, 23], "id": [7, 13, 30, 31], "ida": [26, 28], "idea": [0, 1, 2, 3, 4, 6, 9, 10, 12, 13, 20, 22, 23, 29, 30, 31], "ideal": [0, 2, 6, 8, 13, 25, 28, 31], "idem": 6, "ident": [5, 6, 12, 13, 17, 18, 22, 29, 30], "identifi": [0, 1, 7, 9, 11, 12, 13, 14, 28, 29], "idx": [], "ieor": 25, "ifi": 27, "ifs": [21, 28], "ignor": [0, 1, 3, 9, 15, 29, 31], "ii": [22, 25], "iii": [22, 28], "ij": [0, 1, 3, 6, 8, 12, 14, 16, 22, 25, 28, 29, 31], "ik": [0, 22, 28, 29], "iki": [], "ill": 31, "illustr": [5, 7, 10, 12, 13, 14, 20, 21, 28], "ilsvrc": 31, "im": 6, "imag": [1, 3, 4, 6, 9, 11, 12, 14, 27, 28], "image_at_epoch_": 4, "image_batch": 4, "image_height": 3, "image_path": [0, 6, 7, 9, 28], "image_width": 3, "imageio": 6, "imagenet": 31, "images_from_seed_imag": 4, "imagin": 1, "immedi": [0, 3, 4, 6, 21, 28, 31], "implement": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 19, 20, 23, 25, 28, 29, 30, 31], "impli": [3, 5, 6, 7, 13, 22, 29, 30, 31], "implicit": [3, 31], "implicitli": [11, 25], "import": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 23, 25, 31], "importantli": 3, "importerror": [], "impos": [0, 6, 11, 12, 28], "imposs": [0, 5, 28, 29, 30], "impract": 31, "impress": [0, 12, 28], "improv": [0, 4, 5, 9, 10, 11, 13, 15, 23, 29, 30], "impur": 9, "imread": 6, "imshow": [1, 3, 4, 6], "in3050": [27, 28], "in3310": 28, "in4080": [27, 28], "in4300": [27, 28], "in4310": 27, "in5400": 3, "in5550": 27, "in_out_neuron": 4, "inaccur": [13, 30], "inact": 12, "inadequ": [0, 28], "inappropri": 31, "inch": [6, 29], "incident": [], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 15, 16, 17, 18, 19, 20, 21, 25, 26, 27, 28, 29, 30], "include_bia": [6, 9], "incom": [12, 16], "incorrect": 1, "incoveni": 8, "increas": [0, 1, 3, 4, 5, 6, 9, 12, 13, 19, 23, 25, 28, 29, 31], "increasingli": 25, "increment": 31, "ind": 6, "inde": [0, 2, 4, 5, 6, 13, 28, 29, 30], "indefinit": 4, "independ": [0, 5, 6, 7, 8, 12, 13, 25, 28, 29, 30, 31], "index": [0, 1, 3, 4, 10, 14, 21, 22, 23, 25, 27, 28], "index_col": [0, 28], "indic": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 16, 23, 28, 29], "indirect": [], "indispens": 6, "individu": [1, 6, 7, 10, 12, 25, 28, 29, 31], "indu": [], "indx": 22, "indx1": 2, "indx2": 2, "indx3": 2, "ineffici": [3, 13], "inequ": [8, 13], "inequaltii": 30, "inertia": 13, "inf1000": [21, 28], "inf1100": [21, 28], "inf1100l": [21, 28], "inf1110": [21, 28], "inf3000": 28, "infeas": [9, 31], "infer": [0, 1, 4, 6, 27, 28], "inferenc": 1, "infil": [0, 6, 7, 9, 28], "infin": [5, 6, 7, 11, 19, 29, 30], "infinit": [3, 31], "infinitesim": 25, "influenc": [6, 10, 18], "influenti": 1, "info": 28, "inform": [0, 1, 3, 4, 6, 9, 11, 12, 13, 14, 22, 23, 27, 28, 30, 31], "inforom": 15, "infrequ": 31, "infti": [3, 6, 13, 25, 30], "ingeni": [13, 30, 31], "ingredi": [0, 9, 28], "inher": [6, 31], "inherit": [22, 28, 31], "init": [], "initi": [0, 1, 2, 6, 10, 13, 14, 18, 22, 25, 28, 30, 31], "inject": 14, "inlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 25, 28, 29, 30, 31], "inner": [0, 13, 29], "innerhtml": [], "inp": 4, "inplac": 13, "input": [0, 1, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 23, 25, 28, 29, 30, 31], "input_dim": 1, "input_shap": [3, 4], "inputs": 1, "inputs_shuffl": [0, 1, 29], "inquiri": 20, "insert": [3, 5, 6, 8, 10, 25, 29, 30], "insid": [4, 7], "insight": [0, 1, 5, 21, 28, 29, 30], "insist": [6, 13, 29, 31], "inspir": [0, 1, 12, 23, 28], "instabl": 2, "instal": [0, 1, 5, 6, 9, 15, 20], "instanc": [0, 1, 2, 4, 6, 9, 11, 13, 16, 28, 29, 30, 31], "instanti": 10, "instead": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 17, 20, 22, 25, 28, 29, 31], "institut": 1, "instruct": [0, 1, 15], "int": [0, 1, 2, 3, 4, 5, 6, 11, 13, 14, 22, 25, 29, 31], "int32": 10, "int_": [3, 6, 25], "int_0": 25, "int_a": 25, "intak": [0, 29], "integ": [1, 2, 13, 14, 22, 25, 28], "integer_vector": 1, "integr": [3, 6, 25, 28], "intellig": [0, 14, 27, 28], "intend": 10, "intens": [1, 18], "intention": 14, "interact": [0, 6, 9, 12, 21, 23, 28], "intercept": [0, 6, 8, 11, 13, 16, 17, 18, 19, 28, 29, 30, 31], "intercept_": [0, 6, 8, 9, 13, 28, 29, 31], "interchang": [5, 12, 22], "interconnect": 1, "interesit": 19, "interest": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 21, 23, 25, 28, 29, 30], "interfac": [0, 1, 15, 22, 29], "interior": [0, 9, 28], "intermedi": [22, 29, 31], "intern": [1, 10, 12], "internation": [], "interpol": [1, 3, 4, 6, 12], "interpr": [5, 29, 30], "interpret": [0, 1, 6, 9, 10, 12, 13, 15, 16, 22, 23, 25], "interrupt": [], "interv": [0, 3, 5, 6, 7, 13, 19, 25, 28, 29, 30], "intial": [13, 30], "intract": [0, 4, 29], "intrins": [3, 11, 22, 25, 28], "intro": [21, 27, 28], "introduc": [0, 1, 5, 6, 8, 10, 12, 22, 23, 25, 28, 30, 31], "introduct": [1, 2, 4, 13, 27, 29, 30, 31], "introductori": [0, 4, 22, 27, 28, 29], "intuit": [0, 5, 6, 8, 12, 13, 23, 28, 31], "inv": [0, 5, 13, 17, 28, 29, 30, 31], "invalid": [], "invalu": [0, 13, 21, 28, 30], "invari": 1, "invd": 5, "inver": 8, "invers": [0, 3, 6, 13, 28, 29, 30, 31], "inverse_transform": 8, "invert": [0, 5, 7, 10, 13, 16, 18, 28, 31], "investig": [], "invh": [13, 31], "invok": 8, "involv": [0, 2, 6, 7, 11, 12, 28, 29, 31], "io": [0, 21, 23, 24, 26, 27, 28, 29], "ion": [], "ip": [0, 8, 25, 28], "ipca": 11, "ipynb": [21, 28], "ipython": [0, 5, 7, 9, 11, 14, 21, 23, 28, 29], "iq": 6, "iri": [8, 9], "irreduc": 6, "irrelev": [5, 29, 30], "irrespect": [0, 28], "irvin": 23, "isaac": [], "isaacmus": [], "iseffici": [], "isn": 5, "isnul": [], "isomap": 11, "issu": [1, 9, 15, 22, 31], "it_arrai": 13, "item": [0, 13, 28], "items": [22, 28], "iter": [1, 2, 4, 6, 8, 13, 14, 18, 23, 25, 30, 31], "its": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 21, 22, 23, 25, 28, 30, 31], "itself": [5, 6, 12, 19, 23, 25, 28, 29], "j": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 22, 23, 25, 27, 28, 29, 30, 31], "j1": 22, "j_": 6, "j_lasso_sk": 6, "j_ridge_sk": 6, "j_sk": 6, "jackknif": [6, 21, 28], "jacobian": [2, 13, 30], "janko": [], "jason": 4, "javascript": [], "jax": [21, 28, 31], "jeff": [], "jensen": [26, 28, 29, 30, 31], "jerom": [19, 23, 27], "jhauser": [], "ji": [12, 22], "jit": 13, "jj": [0, 5, 6, 28], "jk": [0, 1, 6, 12, 22, 28], "jl": [0, 28], "jm": 22, "jnp": 13, "job": [2, 8, 10, 15], "join": [0, 4, 6, 7, 9, 28], "joint": [4, 5], "jonathan": [], "json": [], "judg": [13, 30], "judgement": 6, "julia": [21, 22, 23], "jump": [25, 31], "junk": 4, "jupit": 28, "jupyt": [0, 15, 16, 19, 21, 23, 27, 28], "jupyterbook": [], "jupytext": [], "just": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 21, 25, 28, 29, 30, 31], "justif": 0, "justifi": [3, 10], "k": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 22, 23, 25, 26, 28, 29, 30, 31], "k0": 7, "k1": 7, "kaggl": [6, 23], "kappa_d": 25, "karl": [26, 28], "karush": 8, "katex": [], "katrin": [26, 28], "keep": [0, 1, 4, 5, 6, 11, 13, 14, 15, 18, 22, 23, 28, 29, 30, 31], "keepdim": [1, 6, 10, 22], "kei": [1, 3, 6, 12, 31], "kellei": [], "kenneth": [], "kept": [4, 6, 14], "kera": [0, 4, 21, 23, 28], "kernel": [0, 1, 3, 21, 28, 29], "kernel_regular": [1, 3], "kernel_s": 4, "kernelpca": 11, "kev": [0, 28], "kevin": [27, 28], "keyword": [18, 22, 28], "kfold": 6, "kg": 1, "ki": 22, "kick": [1, 13, 31], "kiener": 2, "kilomet": [6, 29], "kim": [], "kind": [0, 2, 3, 4, 8, 12, 13, 14, 28, 29], "kingma": 31, "kj": [6, 12, 22, 29, 31], "kjm": [21, 28], "kkt": 8, "kl": 25, "km": [12, 28], "kmean": 14, "kmeanspoint": 14, "kn_k": 14, "know": [0, 1, 2, 5, 6, 8, 13, 15, 16, 17, 19, 20, 21, 28, 29, 30], "knowledg": [0, 21, 28], "known": [1, 3, 4, 5, 6, 7, 8, 9, 12, 18, 22, 23, 25, 27, 29, 31], "kondev": [0, 28], "kp": 25, "kpca": 11, "kramdown": [], "kroneck": 14, "kt": [], "kuhn": 8, "kvalsund": [26, 28], "kwown": [0, 28], "l": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 22, 23, 25, 28, 30, 31], "l0": 7, "l1": [0, 1, 3, 7, 28], "l1_l2": [1, 3], "l1regl": 5, "l2": [1, 3], "l_": [22, 31], "l_1": 7, "l_2": [7, 13, 30, 31], "l_i": 31, "l_j": 12, "la": 13, "la_": [], "la_i": 12, "la_k": 12, "lab": [20, 21, 23, 28], "label": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 20, 21, 22, 23, 25, 28, 29, 30, 31], "labelencod": [7, 10], "labels": [6, 8, 9], "labels_shuffl": [0, 1, 29], "laboratori": 24, "lack": [0, 28, 31], "lagari": 2, "lagrang": [8, 11], "lam": 18, "lambda": [0, 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 17, 18, 19, 20, 23, 25, 28, 29, 30, 31], "lambda_": 11, "lambda_0": 11, "lambda_1": [5, 8, 11, 29, 30], "lambda_2": [8, 11], "lambda_i": [8, 11], "lambda_iy_i": 8, "lambda_jy_iy_j": 8, "lambda_k": 8, "lambda_n": [5, 8, 29, 30], "lamda": 1, "land": 8, "landmark": 8, "landscap": [13, 18, 30, 31], "langl": [0, 6, 11, 25, 28, 29], "languag": [0, 1, 4, 8, 21, 22, 23, 27, 28], "lapack": [22, 28], "laplac": 5, "laptop": [15, 21], "larg": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 13, 18, 21, 22, 23, 25, 27, 28, 29, 30, 31], "larger": [0, 3, 5, 6, 8, 10, 11, 13, 17, 25, 28, 29, 30, 31], "largest": [4, 8, 11], "lasso": [0, 7, 21, 28, 31], "lasso_sk": 6, "last": [0, 1, 3, 4, 5, 6, 7, 8, 12, 16, 17, 19, 22, 23, 25, 26, 28, 30], "latent": 4, "latent_dim": 4, "latent_point": 4, "latent_space_value_rang": 4, "later": [0, 1, 4, 7, 8, 12, 13, 14, 15, 19, 21, 23, 28, 31], "latest": [4, 15, 21], "latest_checkpoint": 4, "latex": [20, 28], "latexcodec": [], "latter": [0, 3, 6, 7, 8, 11, 13, 22, 25, 28, 29, 30, 31], "lattic": 12, "law": 0, "layer": [0, 4, 13, 28, 31], "lbfg": [7, 9, 10], "lc_messag": [], "lcc": [5, 6], "lda": 11, "ldot": [0, 6, 11, 23, 28], "le": [5, 7, 10, 13, 17, 25, 29, 30, 31], "lead": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 22, 25, 28, 29, 30, 31], "leaf": 9, "leaki": 1, "leakyrelu": 4, "lear": [13, 30], "learn": [3, 4, 5, 6, 7, 8, 9, 10, 12, 22, 26, 27], "learnabl": 3, "learner": 10, "learnig": 28, "learning_r": [8, 10], "learning_rate_init": [0, 1, 28], "learning_schedul": [13, 31], "learnt": 23, "least": [0, 7, 8, 10, 11, 17, 18, 21, 22, 25], "leat": [13, 31], "leav": [0, 1, 3, 5, 6, 9, 11, 28, 30], "lectur": [0, 1, 5, 10, 11, 12, 13, 21, 22, 23, 24, 26, 27, 29], "lecturenot": [0, 21, 23, 27, 28], "left": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 22, 23, 25, 28, 29, 30, 31], "leftarrow": [8, 12], "legend": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 15, 28, 29, 30, 31], "leinonen": 28, "len": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 17, 22, 28, 29, 30, 31], "length": [0, 1, 3, 4, 8, 9, 13, 16, 21, 28, 29, 30, 31], "length_of_sequ": 4, "leq": [0, 5, 7, 8, 13, 14, 25, 28, 29, 30, 31], "less": [0, 1, 3, 4, 5, 6, 8, 9, 13, 21, 25, 28, 29, 30, 31], "lessen": 1, "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 22, 25, 28, 29, 30, 31], "letter": [0, 16, 22, 25, 28, 29], "level": [0, 1, 5, 6, 9, 21, 22, 23, 24, 26, 28, 31], "leverag": 31, "lexer": [], "li": [8, 11], "liabil": [], "liabl": [], "lib": [], "liberti": 31, "liblinear": 10, "librari": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 22, 23, 25, 27, 29, 30, 31], "licenc": [], "licens": [0, 1, 21, 23, 28], "lie": [0, 6, 11, 25, 28, 29], "life": [0, 1, 8, 12, 28], "lifetim": 13, "light": [], "like": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 23, 25, 28, 29, 30, 31], "likelihood": [0, 1, 5, 9, 28, 29], "lim_": 25, "limit": [0, 5, 6, 8, 12, 22, 23, 28, 29], "lin_clf": 8, "lin_model": [], "lin_reg": 9, "linalg": [0, 2, 5, 6, 8, 11, 13, 17, 22, 25, 28, 29, 30, 31], "line": [0, 3, 6, 8, 11, 13, 15, 16, 20, 28, 30, 31], "line1": 8, "line2": 8, "line2d": [], "line3": 8, "line_model": 15, "line_ms": 15, "line_predict": 15, "linear": [1, 3, 5, 6, 7, 9, 10, 11, 12, 16, 17, 18, 19, 21, 23, 25, 31], "linear_model": [0, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 28, 29, 30, 31], "linear_regress": 6, "linearli": [5, 29, 30, 31], "linearloc": [6, 13, 30, 31], "linearregress": [0, 6, 7, 9, 15, 16, 19, 28, 29, 31], "linearsvc": 8, "lineat": 30, "liner": [1, 3], "linerar": 10, "linewidth": [0, 2, 4, 6, 8, 9, 10], "link": [0, 4, 9, 12, 15, 20, 21, 23, 24, 26, 28], "linlag": 5, "linpack": [22, 28], "linreg": [0, 28], "linspac": [0, 2, 3, 4, 6, 8, 9, 10, 13, 16, 17, 19, 22, 25, 28, 29, 31], "linu": 4, "linux": [0, 1, 21, 23, 28], "liquid": [0, 28], "list": [1, 2, 3, 4, 9, 15, 21, 23, 28, 31], "listedcolormap": [9, 10], "literatur": [1, 7, 14, 27], "littl": [1, 3, 9, 12, 31], "live": [8, 16], "ll": [0, 18, 25, 28, 29], "lle": [0, 29], "llm": 20, "lloyd": [4, 14], "lmb": [0, 2, 5, 6, 29, 30, 31], "lmbd": [0, 1, 3, 28], "lmbd_val": [0, 1, 3, 28], "lmbda": [13, 30, 31], "ln": [1, 13, 30], "load": [1, 4, 6, 7, 9, 10, 31], "load_boston": [], "load_breast_canc": [1, 7, 9, 10, 11], "load_data": [3, 4], "load_digit": [1, 3], "load_iri": [8, 9], "loc": [3, 6, 7, 8, 9, 10, 28], "local": [0, 1, 3, 7, 12, 13, 15, 29, 30, 31], "locat": [2, 3, 8, 15], "log": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 13, 15, 20, 22, 23, 28, 31], "log10": [0, 5, 6, 29, 30, 31], "log_": [0, 28], "log_clf": 10, "logarithm": [0, 5, 7, 17, 22, 28], "logbook": 23, "logic": [0, 1, 9, 28], "login": 15, "logist": [0, 1, 2, 8, 9, 10, 11, 12, 13, 21, 29, 30, 31], "logisticregress": [7, 9, 10, 11], "logit": 7, "logreg": [7, 9, 10, 11], "logspac": [0, 1, 3, 5, 6, 28, 29, 30, 31], "long": [0, 1, 3, 4, 12, 13, 28, 30, 31], "longer": [2, 3, 8, 10, 14, 22, 25, 28, 31], "loocv": 6, "look": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 20, 22, 23, 25, 28, 29, 30, 31], "loop": [1, 4, 6, 10, 12, 14, 16, 17, 18, 21, 22, 28, 31], "lose": 1, "loss": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 13, 18, 22, 23, 28], "loss_fil": 4, "lossfil": 4, "lost": 4, "lot": [1, 4, 6, 16, 19, 20, 31], "low": [0, 6, 9, 10, 11, 23, 28, 29], "lower": [0, 1, 3, 6, 9, 10, 16, 22, 29, 31], "lowercas": [22, 28], "lowest": [9, 13, 25, 31], "lr": [1, 3, 4, 10], "lstat": [], "lstm": 4, "lstm_2layer": 4, "lstsq": [0, 28, 29], "lt": 6, "lu": [0, 5, 28, 29, 30], "lubksb": 22, "luckili": 2, "ludcmp": 22, "lux": 22, "lvert": 1, "lw": [0, 28], "m": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 15, 22, 25, 26, 27, 28, 29, 30, 31], "m_": [9, 12], "m_0": 31, "m_1": 14, "m_h": [0, 28], "m_k": 14, "m_l": 12, "m_n": [0, 28], "m_p": [0, 28], "m_t": [13, 31], "ma": 11, "machin": [1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 15, 16, 22, 27, 29, 31], "machinelearn": [0, 6, 16, 20, 21, 23, 24, 26, 27, 28, 29, 30], "machineri": [], "mackai": 27, "macro": [], "made": [0, 1, 3, 4, 5, 6, 7, 9, 11, 12, 23, 28, 29, 31], "mae": [0, 28], "magic": 4, "magnitud": [1, 6, 7, 13, 29, 31], "mai": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 19, 21, 22, 23, 25, 28, 29, 30, 31], "mail": [24, 26], "main": [0, 1, 3, 4, 5, 6, 7, 9, 22, 23, 27, 29, 30, 31], "mainli": [0, 5, 6, 7, 9, 28, 29], "maintain": [6, 31], "major": [1, 6, 9, 10, 13, 22, 28, 30, 31], "make": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 18, 19, 21, 22, 23, 25, 27, 28, 30, 31], "make_axes_locat": 6, "make_moon": [8, 9, 10], "make_pipelin": [0, 6, 10, 29], "makedir": [0, 6, 7, 9, 28], "malcondit": 22, "malign": [1, 7, 9], "mammographi": 5, "manag": [0, 2, 3, 15, 21, 23, 28, 31], "mandatori": [26, 28], "mani": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 27, 28, 29, 30, 31], "manifold": 11, "manner": 3, "manual": [6, 29, 31], "map": [0, 1, 2, 6, 7, 8, 11, 12, 14, 25, 28], "marc": 29, "margin": [0, 5, 8], "marit": [0, 28], "mark": 28, "markdownfil": [], "markdownit": [], "markdownitdeflist": [], "markedli": [], "marker": [7, 22, 28], "markov": [21, 28], "markup": [], "marsaglia": 25, "mass": [0, 1, 5, 13, 29, 30], "massag": [0, 28], "masses2016": [0, 28], "masses2016ol": [0, 28], "masses2016tre": 0, "masseval2016": [0, 28], "master": [24, 26], "mat": [21, 28], "mat1100": [21, 28], "mat1110": [21, 28], "mat1120": [21, 28], "match": [1, 4, 5, 13, 14, 15, 29, 30, 31], "materi": [4, 5, 7, 13, 15, 22, 24, 26], "math": [3, 7, 12, 13, 22, 25, 27, 28, 31], "mathbb": [0, 4, 5, 6, 7, 8, 11, 12, 13, 14, 17, 19, 22, 23, 25, 28, 29, 30, 31], "mathbf": [0, 5, 6, 7, 8, 13, 19, 22, 23, 28, 29, 30, 31], "mathcal": [1, 5, 6, 7, 13, 23], "matheemat": 3, "mathemat": [0, 6, 11, 12, 13, 21, 22, 25, 27, 28, 31], "mathemati": 28, "mathrm": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 23, 25, 28, 29, 30, 31], "matmul": [1, 2, 5], "matnat": 27, "matplotlib": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 23, 25, 28, 29, 30, 31], "matric": [0, 1, 3, 4, 6, 7, 8, 11, 13, 16, 17, 21, 29, 30], "matrix": [0, 2, 3, 4, 6, 7, 8, 10, 13, 17, 18, 19, 23, 25], "matshow": 1, "matter": [2, 3, 13, 29, 30, 31], "matthia": [], "max": [0, 1, 2, 3, 4, 9, 10, 12, 13, 26, 28, 30, 31], "max_depth": [0, 9, 10], "max_diff": 2, "max_diff1": 2, "max_diff2": 2, "max_it": [0, 1, 8, 13, 28], "max_iter": 14, "max_leaf_nod": 10, "max_sampl": 10, "maxdegre": [0, 6, 10, 29], "maxdepth": 10, "maxim": [1, 4, 5, 7, 8, 11], "maximum": [0, 2, 3, 5, 7, 8, 9, 10, 13, 14, 28, 29, 30, 31], "maxpolydegre": [5, 6, 29, 30, 31], "maxpooling2d": 3, "mbox": [5, 6, 29, 30], "mcculloch": 12, "md": 11, "mdoel": 4, "me": [], "mean": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 21, 22, 23, 25, 28, 31], "mean_absolute_error": [0, 28], "mean_divisor": 14, "mean_i": 25, "mean_matrix": 14, "mean_squared_error": [0, 4, 6, 7, 10, 15, 19, 28, 29], "mean_squared_log_error": [0, 28], "mean_vector": 14, "mean_x": 25, "meaning": [0, 4, 7, 28], "meansquarederror": [0, 28], "meant": [3, 7, 10, 13], "meanwhil": 31, "measur": [0, 1, 2, 5, 6, 9, 11, 12, 14, 16, 18, 19, 23, 25, 28, 29, 31], "mechan": [0, 4, 25, 28, 31], "median": [0, 28, 29, 31], "medicin": 12, "medium": [4, 8, 13, 31], "medv": [], "meet": [0, 26], "mehta": [0, 28, 29, 30], "member": 20, "memori": [3, 4, 11, 12, 13, 18, 22], "mentat": [], "mention": [0, 12, 13, 23, 25, 28, 30, 31], "merchant": [], "mere": [0, 23], "merg": [], "meshgrid": [2, 5, 6, 8, 9, 10, 11], "mess": 15, "messag": [5, 13], "messi": 2, "met": [0, 3, 8, 29], "meta": [], "meteorolog": 9, "meter": [6, 29], "method": [0, 1, 2, 3, 4, 5, 7, 8, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 25, 27, 29], "metion": 6, "metric": [0, 1, 3, 6, 7, 9, 10, 14, 15, 28, 29], "metropoli": [21, 28], "mev": [0, 25, 28], "mgd": [13, 31], "mglearn": [21, 28], "mgrid": 13, "mhjensen": [], "mi": 10, "mia": [26, 28], "michael": [], "microsoft": 27, "mid": 1, "midel": 4, "midnight": 15, "midpoint": 9, "might": [0, 1, 2, 4, 6, 9, 13, 15, 17, 18, 29, 30, 31], "migth": 17, "mild": 9, "millimet": [6, 29], "million": [0, 28, 29, 31], "mimic": 12, "min": [0, 2, 5, 8, 9, 30], "min_": [0, 2, 5, 14, 17, 28, 29, 30], "min_samples_leaf": 9, "mind": [0, 6, 13, 15, 18, 28, 29, 30, 31], "mindboard": 4, "mine": [21, 28], "mini": [1, 11, 12, 13, 30], "minibatch": [1, 11, 13], "minibathc": [13, 31], "miniforge3": [], "minim": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 29, 30, 31], "minima": [0, 1, 7, 13, 28, 30, 31], "minimum": [0, 1, 2, 6, 8, 9, 11, 13, 29, 30, 31], "minmaxscal": [0, 29, 31], "minor": 25, "minst": 1, "minu": 7, "mirjalili": 28, "mirror": 9, "misc": 6, "misclassif": [8, 9, 10], "misclassifi": [8, 10], "miser": 0, "mismatch": 1, "miss": [7, 10], "mistak": [4, 19], "mit": 27, "mitig": 31, "mix": [1, 2, 28], "mixtur": [13, 31], "mk": [9, 22], "mkdir": [0, 6, 7, 9, 28], "ml": [0, 1, 10, 13, 22, 23, 29, 30, 31], "mlab": 25, "mle": [5, 7], "mlp": 1, "mlpclassifi": 1, "mlpregressor": [0, 28], "mm": 22, "mml": 29, "mn": [12, 25], "mnist": [1, 11], "mo": [], "mod": 25, "mode": [24, 26, 28], "model": [2, 3, 5, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 20, 21, 23, 25, 27, 29, 30, 31], "model_select": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "moder": [10, 31], "modern": [0, 6, 7, 21, 28, 31], "modest": 31, "modif": [2, 12, 13], "modifi": [0, 1, 3, 5, 7, 8, 10, 12, 13, 28, 29, 30, 31], "modul": [0, 16, 22, 28], "modular": 25, "modulo": 25, "moe": [11, 29], "moment": [5, 6, 13, 25], "mondai": [26, 28], "monitor": [13, 31], "monoton": [5, 12, 25], "mont": [0, 6, 21, 25, 27, 28], "montli": 16, "moor": [5, 6], "more": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 25], "moreov": [0, 3], "morten": [26, 28, 29, 30, 31], "mortenhj": 28, "most": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 21, 23, 25, 28, 29, 30, 31], "mostli": [1, 11, 18, 31], "motion": [0, 13], "motiv": [1, 4], "moulin": 31, "move": [0, 4, 5, 6, 7, 9, 12, 13, 14, 15, 16, 23, 25, 29, 30], "mpl": [7, 28], "mpl_toolkit": [2, 6, 13, 30, 31], "mplot3d": [2, 6, 13, 30, 31], "mplregressor": 1, "mse": [0, 4, 5, 6, 9, 10, 15, 16, 17, 19, 20, 23, 28, 29, 30, 31], "mse_simpletre": 10, "mselassopredict": [5, 30], "mselassotrain": [5, 30], "mseownridgepredict": [6, 29, 30, 31], "msepredict": [5, 30], "mseridgepredict": [0, 5, 6, 29, 30, 31], "msetrain": [5, 30], "msg": [], "msle": [0, 28], "mt": [7, 12], "mu": [0, 6, 11, 13, 25, 28, 31], "mu0": 25, "mu1": 25, "mu2": 25, "mu_": [6, 25, 29, 31], "mu_i": [6, 29, 31], "mu_n": 11, "mu_x": 25, "much": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 20, 22, 23, 25, 28, 29, 30, 31], "multi": [0, 1, 3, 7, 21, 28], "multiclass": [1, 7], "multidimension": [11, 12, 28], "multilay": 1, "multinomi": 7, "multipl": [2, 4, 5, 6, 7, 12, 13, 15, 25, 29, 30, 31], "multipli": [3, 5, 6, 11, 13, 18, 22, 25, 29, 30, 31], "multiplum": 8, "multivari": [0, 2, 10, 11, 21, 25, 28], "multivariate_norm": [11, 14], "multpli": 16, "murphi": [11, 27, 28], "muse": [], "must": [1, 2, 5, 6, 8, 10, 12, 13, 14, 15, 20, 25, 29, 30, 31], "mutat": 7, "mutual": [1, 3, 6, 13], "mx_": 25, "my": 28, "myenv": [], "myriad": [0, 21, 28], "mz1": 25, "mz2": 25, "m\u00f8svatn": 6, "n": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "n1": 22, "n2": 22, "n8grai": [], "n_": [1, 2, 3, 8, 12, 25], "n_0": [12, 25], "n_boostrap": [6, 10], "n_bootstrap": 6, "n_categori": [1, 3], "n_cluster": 14, "n_compon": 11, "n_epoch": [13, 31], "n_estim": 10, "n_examples_to_gener": 4, "n_featur": [1, 18], "n_filter": 3, "n_hidden": 2, "n_hidden_neuron": [0, 1, 28], "n_i": 25, "n_input": [0, 1, 3, 29], "n_instanc": 9, "n_iter": 31, "n_job": 10, "n_k": 14, "n_l": [12, 25], "n_layer": 1, "n_m": 9, "n_neuron": 1, "n_neurons_connect": 3, "n_neurons_layer1": 1, "n_neurons_layer2": 1, "n_point": 14, "n_sampl": [6, 8, 9, 10, 14, 18], "n_split": 6, "n_step": 4, "n_t": 2, "n_x": 2, "nabla": [1, 13, 30, 31], "nabla_": [2, 13, 30, 31], "nabla_w": 13, "nag": 13, "naimi": [0, 28], "naiv": 7, "naive_kmean": 14, "name": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 18, 20, 21, 22, 23, 25, 26, 28, 29, 30], "namespac": [], "narrow": [13, 31], "nathaniel": [], "nation": [1, 5], "nativ": [21, 28], "natur": [0, 1, 4, 8, 9, 12, 13, 23, 25, 27, 28, 30, 31], "navier": 12, "navig": [15, 31], "nb": 25, "nb_": 22, "nbconvert": 28, "nd": 14, "ndarrai": 6, "ne": [9, 10, 22, 25, 29, 30], "nearest": [1, 3, 6, 11], "nearli": [13, 30], "neat": 28, "neccesari": 6, "necess": 2, "necessari": [0, 1, 3, 4, 8, 14, 18, 28], "necessarili": [0, 4, 11, 25, 28], "necesserali": 5, "neck": 7, "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 22, 25, 29, 30, 31], "neg": [0, 1, 3, 5, 6, 7, 10, 13, 22, 25, 28, 30], "neg_mean_squared_error": 6, "neglect": [25, 31], "neglig": 25, "neighbor": [3, 6, 11], "neither": [4, 13, 31], "neq": [13, 14, 25, 30], "nervou": 12, "nest": [9, 12], "nesterov": 13, "net": [2, 4, 12], "netlib": [22, 28], "network": [0, 9, 13, 21, 27, 29], "neural": [0, 13, 21, 27, 29], "neural_network": [0, 1, 2, 28], "neuralnetwork": 1, "neuron": [1, 2, 3, 4, 12], "neutral": [0, 28], "neutron": [0, 28], "never": [1, 4, 6, 9, 25], "new": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 20, 22, 28, 29, 30, 31], "new_chang": [13, 31], "new_hobbit": 28, "newaxi": [0, 3, 6, 9], "newli": [0, 28], "newlin": [], "newton": [1, 7, 8, 13, 25], "next": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 28, 29, 30, 31], "next_guess": 13, "next_input": 4, "ng": 1, "ni": 14, "nice": [0, 1, 5, 11, 28, 29, 30], "nicer": [18, 31], "nip": 31, "niter": [13, 30, 31], "nitric": [], "nlambda": [0, 5, 6, 29, 30, 31], "nlp": 27, "nm": 25, "nm_n": [0, 28], "nmse": 6, "nn": [2, 5, 6, 12, 22, 28], "nn_model": 1, "nnmin": 2, "node": [1, 3, 9, 10, 12], "nois": [0, 4, 5, 6, 8, 9, 10, 13, 18, 19, 23, 28, 29, 30, 31], "noise_dimens": 4, "noisi": [1, 6, 23, 31], "non": [0, 1, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 22, 25, 28, 29, 30], "nondifferenti": 31, "none": [0, 1, 2, 4, 5, 9, 10, 13, 25, 28, 29], "noninfring": [], "nonlinear": [3, 6, 8, 9, 11, 12], "nonneg": [6, 9, 13, 30], "nonparametr": 6, "nonsens": 25, "nonsingular": 22, "nonumb": [3, 7, 8, 13, 22], "nor": [1, 4, 13, 31], "norm": [0, 1, 5, 6, 8, 11, 13, 18, 28, 29, 30, 31], "normal": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "normali": [22, 28], "norwai": [6, 23, 28, 30, 31], "notat": [0, 2, 5, 6, 13, 14, 25, 28, 29, 30], "note": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 25, 27, 28, 31], "notebook": [0, 1, 3, 9, 15, 16, 19, 20, 21, 23, 28], "noteworthi": 31, "noth": [1, 2, 5, 8, 12, 14, 25, 29, 30], "notic": [4, 5, 12, 13, 22, 25, 28], "notion": 3, "novel": [3, 6, 10, 28], "novemb": [1, 26, 28], "now": [0, 2, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 19, 21, 22, 23, 25, 28, 29], "nowadai": [0, 1, 3, 9, 21, 28], "nox": [], "np": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 22, 25, 28, 29, 30, 31], "npm": [], "npr": 2, "nsampl": 6, "nt": 2, "nu": 25, "nuclear": [5, 29, 30], "nuclei": [0, 25, 28], "nucleon": [0, 28], "nucleu": [0, 28], "num": 4, "num_coordin": 2, "num_hidden_neuron": 2, "num_it": [2, 18], "num_neuron": 2, "num_neurons_hidden": 2, "num_point": 2, "num_tre": 10, "num_valu": 2, "number": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 22, 23, 24, 26, 28, 30], "numberid": 7, "numberparamet": 3, "numer": [0, 5, 6, 9, 10, 11, 12, 13, 21, 22, 27, 28, 29, 30, 31], "numpi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 23, 25, 29, 30, 31], "numpydocstr": [], "nunmpi": [5, 29], "nve_frngahw": 30, "nx": 2, "ny": 25, "o": [0, 1, 4, 5, 6, 7, 8, 9, 11, 22, 26, 27, 28, 29, 30, 31], "obei": [6, 11, 13, 29, 31], "object": [0, 1, 4, 8, 10, 15, 19, 22, 28, 31], "obliqu": [5, 29, 30], "observ": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 25, 28, 30, 31], "obtain": [0, 1, 5, 6, 7, 8, 9, 10, 12, 13, 14, 17, 22, 23, 25, 28, 29, 30, 31], "obviou": [5, 6, 11, 25, 29, 30], "obviouli": 28, "obvious": [0, 4, 5, 6, 22, 28], "oc": [29, 30], "occupi": [], "occur": [0, 6, 8, 9, 22, 25, 28], "octob": [26, 28], "od": 0, "odd": [0, 3, 7, 28, 29, 31], "odenum": 2, "odesi": 2, "oen": 0, "off": [1, 3, 4, 5, 9, 13, 20, 25, 31], "offer": [6, 11, 21, 22, 24, 26, 28], "offic": [26, 28], "offici": [24, 28], "often": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "ofter": [22, 28], "ol": [0, 13, 17, 19, 29, 31], "old": [1, 5, 10, 13, 15, 18], "ols_paramet": 16, "ols_sk": 6, "ols_svd": 6, "olsbeta": 30, "olstheta": [0, 5], "omega": [2, 3, 6], "omega_0": 3, "omit": [0, 5, 28, 29, 30], "onc": [1, 6, 9, 11, 13, 20], "one": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 19, 20, 21, 22, 23, 25, 26, 28, 29, 31], "onehot": 1, "onehot_vector": 1, "onehotencod": 9, "ones": [0, 2, 5, 6, 8, 9, 10, 11, 13, 16, 18, 22, 23, 28, 29, 30, 31], "ones_lik": 4, "ong": 29, "onl": 3, "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 22, 23, 25, 28, 29, 30, 31], "onlin": [11, 15, 20, 24, 31], "onto": [5, 11, 29, 30], "open": [0, 1, 4, 6, 7, 9, 15, 21, 23, 24, 26, 28], "oper": [0, 1, 3, 5, 6, 10, 11, 12, 13, 15, 16, 21, 25, 28, 29, 30, 31], "operation": 25, "oplu": 25, "opmiz": [13, 31], "opportun": 0, "oppos": [6, 13], "opposit": [1, 5, 8, 29, 30], "opt": [1, 5, 23, 28, 30], "optim": [0, 2, 3, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 19, 23], "optimis": [1, 3], "option": [0, 1, 3, 5, 6, 8, 11, 15, 18, 22, 29, 31], "optmiz": [1, 8, 13, 29], "oral": 28, "orang": 0, "order": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 15, 19, 22, 23, 25, 28, 29, 30], "ordinari": [0, 2, 3, 7, 11, 13, 17, 18, 21], "oreilli": [27, 28], "org": [0, 3, 4, 16, 20, 21, 22, 23, 27, 28, 29, 30, 31], "organ": [6, 7, 10, 22], "orient": [1, 5, 25, 29, 30], "origin": [0, 3, 5, 6, 8, 11, 12, 13, 15, 22, 28, 29, 30, 31], "orthogn": [5, 29, 30], "orthogon": [0, 5, 6, 8, 11, 13, 22, 28, 29, 30], "orthonorm": [5, 29, 30], "os": [26, 28], "oscar": 1, "oscil": [3, 13, 31], "oskar": 28, "oskarlei": 28, "osl": 18, "oslo": [0, 21, 23, 24, 26, 28, 29, 30, 31], "osx": [0, 21, 23, 28], "other": [0, 1, 2, 3, 5, 6, 7, 8, 10, 13, 14, 16, 19, 21, 24, 25, 26, 27, 29, 30, 31], "otherwis": [0, 1, 4, 7, 13, 22, 28, 31], "ouput": [5, 7, 12], "our": [1, 2, 3, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 19, 21, 22, 25, 31], "ourmodel": 0, "ourselv": [0, 5, 6, 8, 11, 13, 28, 29, 30], "out": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 21, 22, 23, 25, 28, 29, 31], "out_fil": 9, "outcom": [0, 7, 9, 10, 12, 25, 29], "outdoor": 9, "outer": [6, 12, 13], "outfil": 4, "outlier": [0, 8, 28, 29, 31], "outlin": [6, 10, 11], "outlook": 9, "outperform": [10, 31], "output": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 22, 23, 25, 28, 29, 30, 31], "output_bia": 1, "output_bias_gradi": 1, "output_shap": 4, "output_weight": 1, "output_weights_gradi": 1, "outputlayer1": 12, "outputlayer2": 12, "outsid": 4, "over": [0, 1, 3, 4, 5, 6, 9, 10, 12, 13, 15, 16, 19, 22, 23, 28, 29, 30, 31], "over1": 13, "overal": [1, 10, 31], "overcast": 9, "overcom": [12, 13], "overdetermin": [0, 28], "overfit": [0, 1, 3, 6, 9, 10, 13, 31], "overflow": [5, 31], "overhead": 12, "overlap": [3, 7, 8, 9], "overleaf": 20, "overlin": [0, 5, 6, 9, 10, 11, 14, 22, 28, 29, 31], "overshoot": 31, "overst": 0, "overtrain": 4, "overview": [3, 20], "own": [4, 5, 6, 8, 12, 13, 16, 18, 21, 22, 30, 31], "owner": [], "ownmsepredict": 0, "ownmsetrain": 0, "ownridgebeta": 29, "ownridgetheta": [0, 6, 29, 30, 31], "ownypredictridg": 0, "ownytilderidg": 0, "oxid": [], "p": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 22, 25, 28, 29, 30, 31], "p0": 2, "p1": 2, "p_": [2, 4, 8, 9], "p_hidden": 2, "p_i": [5, 25], "p_j": 25, "p_n": 25, "p_output": 2, "p_x": 25, "pack": [0, 28], "packag": [0, 1, 3, 4, 5, 8, 11, 13, 15, 20, 21, 23, 25, 29, 30, 31], "packtpub": 28, "packtpublish": 28, "pad": [3, 4], "page": [0, 21, 28, 30, 31], "pai": [0, 1, 9, 13, 15, 31], "pair": [0, 2, 3, 9, 21, 25, 28], "paltform": 15, "panda": [0, 4, 5, 6, 7, 9, 11, 21, 23, 30, 31], "pandoc": [], "panel": 28, "paper": [1, 31], "paper_fil": 31, "paradigm": [0, 28], "paragraph": 20, "parallel": [10, 13, 21, 22, 28], "param": 2, "paramat": 2, "paramet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, 18, 19, 23, 25, 30, 31], "parameter": [0, 6, 10, 28, 29], "parametr": [0, 6, 28, 29], "paramt": [3, 5], "parser": [], "part": [0, 1, 3, 5, 6, 10, 17, 19, 20, 22, 24, 25, 26, 28, 29], "partial": [0, 1, 5, 6, 7, 8, 10, 11, 12, 13, 16, 25, 28, 29, 30, 31], "particip": [15, 21, 24, 26, 28], "particl": [0, 4, 13, 25, 28], "particular": [0, 1, 2, 3, 5, 6, 9, 10, 11, 12, 13, 16, 23, 25, 27, 28, 29, 30, 31], "particularli": [5, 6, 8, 11, 13, 25, 29, 30, 31], "partit": [1, 4, 9], "partli": [6, 28], "partner": 15, "pass": [2, 3, 12, 14, 31], "password": 23, "past": [10, 25, 31], "patch": [6, 25], "path": [0, 4, 6, 7, 9, 21, 28, 31], "pathcollect": 17, "patholog": [], "patient": 7, "patter": 4, "pattern": [0, 3, 4, 12, 27, 28, 31], "pauli": [0, 28], "pav": [], "pc": [11, 15, 21], "pca": [0, 7, 21, 28, 29], "pd": [0, 4, 5, 6, 7, 9, 11, 28, 29, 30, 31], "pde": 2, "pdf": [0, 3, 4, 5, 6, 9, 15, 16, 19, 20, 23, 27, 28], "pedagog": [0, 28, 29], "penal": [6, 18, 29, 31], "penalti": [6, 13, 18, 23, 29, 31], "penros": [5, 6], "pentagon": [13, 30], "peopl": [1, 9, 13, 21, 31], "per": [0, 1, 6, 24, 26, 28, 31], "percentag": [10, 11, 26], "perceptron": [0, 1, 7, 28], "peregrin": 28, "perez": [], "perfect": [0, 1, 13, 28, 31], "perfectli": [4, 6], "perform": [0, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 18, 19, 21, 22, 23, 25, 28, 29, 30, 31], "performac": 4, "perhap": [0, 5, 13, 28, 29, 30, 31], "perimet": 1, "period": [1, 4, 25], "permiss": 15, "permit": [], "permut": 11, "persist": 13, "person": [5, 6, 7, 16, 20, 24, 26, 28, 29], "perspect": 27, "pertin": [12, 28], "petal": [8, 9], "peter": [27, 29], "phantom": 25, "phase": [6, 12], "phenomena": 25, "phenomenon": 31, "phi": 8, "phi_k": 8, "philipp": [], "philosophi": 13, "phone": [26, 28], "photo": [4, 28], "php": 23, "phrase": [0, 28], "physic": [0, 1, 4, 7, 12, 13, 25, 26, 27, 28, 29, 30, 31], "pi": [2, 3, 5, 6, 7, 9, 12, 13, 25], "pick": [1, 9, 10, 11, 13, 14, 31], "pickl": 1, "pictur": [0, 28], "pie": [21, 28], "piec": [11, 14], "pillow": [0, 21, 23, 28], "pinv": [5, 6, 13, 23, 29, 30, 31], "pip": [0, 1, 15, 21, 23, 28], "pip3": [0, 1, 23, 28], "pipelin": [0, 6, 8, 10, 29], "pippin": 28, "pit": 4, "pitfal": [6, 29], "pitt": 12, "pixel": [1, 3, 4, 28], "pixel_height": [1, 3], "pixel_width": [1, 3], "pkg_resourc": [], "pkgutil": [], "place": [0, 4, 6, 8, 13, 15, 22, 23, 28, 30], "plai": [0, 3, 4, 5, 6, 8, 11, 18, 21, 23, 28, 29, 30], "plain": [8, 10, 12, 13, 14, 30, 31], "plan": [6, 9, 26, 27, 28], "plane": [8, 9], "plateau": [5, 30, 31], "platform": [21, 28], "plausibl": 12, "pleas": [13, 23, 26, 28], "plenti": 1, "plethora": [3, 12], "plot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "plot_all_sc": [23, 29], "plot_confusion_matrix": [7, 10], "plot_count": 6, "plot_cumulative_gain": [7, 10], "plot_data": 1, "plot_dataset": 8, "plot_decision_boundari": [9, 10], "plot_import": 10, "plot_max": 4, "plot_min": 4, "plot_model": 4, "plot_numb": 4, "plot_predict": 8, "plot_regression_predict": 9, "plot_result": 4, "plot_roc": [7, 10], "plot_surfac": [2, 6, 13], "plot_train": 9, "plot_tre": [9, 10], "plt": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 22, 25, 28, 29, 30, 31], "plu": [0, 3, 5, 7, 18, 28, 29], "plugin": [], "pm": 8, "pmatrix": 2, "pml": 27, "pn": 3, "png": [0, 4, 6, 7, 9, 28], "point": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 20, 22, 23, 25, 26, 28, 29, 30, 31], "point_1": 4, "point_2": 4, "poisson": [21, 25, 28], "poli": [6, 8], "poly100_kernel_svm_clf": 8, "poly3": 0, "poly3_plot": 0, "poly_featur": [8, 9, 15], "poly_features10": 9, "poly_fit": 9, "poly_fit10": 9, "poly_kernel_svm_clf": 8, "poly_model": 15, "poly_ms": 15, "poly_predict": 15, "polydegre": [0, 5, 6, 10, 29], "polygon": [13, 30], "polym": 12, "polymi": 23, "polynomi": [0, 5, 6, 7, 8, 9, 10, 11, 15, 17, 19, 20, 23, 28, 29, 31], "polynomial_featur": [6, 15, 16, 17], "polynomial_svm_clf": 8, "polynomialfeatur": [0, 6, 8, 9, 15, 16, 19, 29], "polytrop": [0, 6], "pool": 3, "pool_siz": 3, "poor": [1, 13, 30, 31], "poorli": [0, 29], "popul": [0, 5, 28, 29], "popular": [0, 1, 3, 6, 7, 8, 9, 11, 12, 15, 21, 22, 23, 25, 29], "popularli": [0, 28], "portabl": 10, "portion": [11, 13, 31], "pose": [0, 4, 5, 6, 11, 25, 28], "posit": [0, 1, 2, 3, 5, 7, 8, 10, 11, 13, 14, 22, 25, 28, 29, 30, 31], "possibl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 23, 25, 26, 28, 29, 30, 31], "possibli": [6, 8, 13, 23], "post": [], "posterior": 5, "postpon": [0, 29], "postscript": 23, "postul": 5, "potenti": [0, 3, 5, 6, 12, 13, 29, 31], "pott": 12, "power": [0, 1, 5, 6, 8, 9, 12, 13, 28, 29, 30, 31], "pp": [5, 6, 19], "practic": [0, 5, 6, 7, 8, 16, 18, 19, 23, 25, 29], "practition": [0, 1, 3, 28, 31], "pre": 28, "preambl": [], "preced": [1, 11, 12, 25], "preceed": 4, "preceq": 8, "precis": [0, 2, 5, 11, 13, 22, 23, 25, 28, 29, 31], "pred": 6, "predicit": 0, "predict": [0, 1, 5, 6, 7, 8, 9, 10, 15, 16, 17, 19, 21, 23, 27, 28, 29, 30, 31], "predict_prob": 1, "predict_proba": [7, 10], "predictor": [0, 5, 6, 7, 9, 10, 11, 28, 29, 31], "prefer": [0, 1, 6, 8, 9, 11, 13, 15, 20, 21, 23, 28], "prepar": [0, 6, 22, 23, 28, 29], "preprocess": [0, 4, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 23], "prerequisit": 0, "prescript": 23, "presenc": 13, "present": [0, 5, 6, 7, 9, 12, 13, 22, 23, 25, 28, 29, 30, 31], "preserv": [3, 11, 22], "press": [13, 15, 27, 30], "pretrain": [1, 4], "pretti": [0, 4, 8, 9, 21, 23, 28], "prettier": [], "prev_centroid": 14, "prevent": [13, 25, 31], "previou": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 22, 23, 25, 29, 30, 31], "previous": [2, 3, 9, 10, 25], "price": [0, 4, 9, 13, 31], "primal": 8, "primari": [0, 7, 28], "prime": 25, "princip": [0, 5, 7, 21, 28, 29, 30], "principl": [0, 6, 7, 8, 14, 28], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 22, 25, 28, 29, 30, 31], "print_funct": [8, 9], "printout": [0, 28], "prior": [0, 5, 6, 28], "privat": 0, "prob": [1, 25], "probabilist": [0, 27, 28, 29], "probabl": [0, 1, 3, 4, 6, 7, 10, 13, 21, 28, 29, 31], "problem": [0, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 19, 21, 22, 23, 25], "probml": 27, "proce": [0, 5, 6, 7, 8, 9, 10, 11, 13, 22, 28, 29], "procedur": [2, 4, 5, 6, 8, 10, 11, 13, 29, 30, 31], "proceed": 22, "process": [0, 2, 4, 6, 9, 10, 12, 13, 21, 22, 23, 25, 27, 28, 30, 31], "procur": [], "prod": 27, "prod_": [1, 5, 7], "produc": [0, 3, 4, 5, 6, 9, 10, 11, 12, 13, 18, 20, 21, 22, 25, 28, 29], "product": [0, 1, 3, 5, 6, 7, 8, 12, 13, 16, 17, 21, 22, 28, 29, 31], "profess": [0, 28], "profit": [], "program": [0, 1, 4, 5, 6, 8, 12, 14, 15, 21, 22, 24, 25, 26, 28, 29], "programm": 22, "progress": [1, 4, 14, 31], "prohibit": 6, "project": [0, 1, 2, 3, 5, 11, 13, 15, 19, 21, 24, 29, 30, 31], "project_root_dir": [0, 6, 7, 9, 28], "promin": 12, "promis": 8, "promot": [26, 28], "prompt": 20, "prone": [9, 15], "pronounc": [13, 21, 28, 31], "proof": [0, 11, 12, 13, 28, 30], "prop": 31, "prop_cycl": [], "propag": [2, 3, 13, 31], "proper": [0, 2, 6, 7, 20], "properli": [1, 6, 8, 10, 13, 18, 20, 23, 31], "properti": [0, 1, 3, 12, 13, 16, 22, 28], "proport": [0, 1, 5, 9, 11, 13, 25, 28, 29], "propos": [1, 4, 6, 10, 23, 28, 31], "propto": [5, 13, 30, 31], "proton": [0, 28], "prove": [3, 13, 30, 31], "provid": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 20, 21, 22, 23, 25, 28, 29, 30, 31], "proxi": [1, 13, 31], "prune": 9, "pseudo": [22, 25, 31], "pseudocod": 23, "pseudoinv": 5, "pseudoinvers": [5, 6, 23], "pseudorandom": [6, 25], "psychologi": [0, 28], "pt": 13, "public": [0, 15, 21, 28], "publish": [], "pull": 15, "punish": [0, 1, 28], "pure": [3, 9, 25], "purest": 9, "puriti": 9, "purpos": [0, 3, 10, 12, 14, 28], "push": 15, "put": [1, 20, 31], "py": 5, "pybtex": [], "pycod": 28, "pydata": 21, "pydevd_extension_api": [], "pydevd_plugin": [], "pydevd_plugin_plugin_nam": [], "pydot": 9, "pygment": [], "pyhton2": 28, "pylab": [7, 28], "pypi": 21, "pyplot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 22, 25, 28, 29, 30, 31], "pythagora": 5, "python": [1, 2, 3, 5, 6, 8, 11, 12, 13, 14, 18, 20, 23, 25, 29, 31], "python2": [0, 23], "python3": [0, 21, 23, 28], "pythonpath": [], "pytorch": [0, 21, 23, 28], "pyzmq": [], "q": [5, 6, 8, 11, 25], "qp": 8, "qquad": [2, 11, 13, 22, 31], "qr": [5, 6, 22, 29, 30], "quad": [1, 13, 22], "quadrat": [0, 8, 9, 13, 28], "qualit": [4, 9, 23, 25], "qualiti": [0, 9, 21, 28, 29], "quantifi": 1, "quantil": 10, "quantit": [0, 6, 9, 23, 28], "quantiti": [0, 2, 5, 6, 7, 9, 10, 11, 12, 14, 16, 22, 25, 28, 29, 30, 31], "quantum": [4, 12, 27, 28], "quartil": [0, 29, 31], "quench": 5, "queri": 9, "question": [0, 5, 6, 9, 11, 12, 13, 23, 26, 28, 29, 31], "qugan": 4, "quick": [4, 25], "quicker": 31, "quickli": [1, 3, 9, 11, 13, 30, 31], "quit": [1, 5, 6, 9, 10, 12, 15, 29, 30], "quot": 4, "r": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 21, 22, 23, 25, 29, 30, 31], "r2": [0, 5, 6, 19, 28, 29, 30], "r2_score": [0, 28], "r2score": [0, 28], "r_": 31, "r_0": 31, "r_1": 9, "r_2": 9, "r_j": 9, "r_m": 9, "r_t": 31, "rad": [], "rade": [], "radial": [8, 12], "radioact": 25, "radiu": [0, 1, 29, 31], "radziej": [], "ragan": [], "rain": 9, "ram": 31, "ramanujam": [], "ramp": 1, "ran0": 25, "ran1": 25, "ran2": 25, "ran3": 25, "rand": [0, 4, 5, 6, 9, 10, 13, 15, 19, 22, 28, 29, 30, 31], "randint": [6, 9, 13, 31], "randn": [0, 1, 2, 5, 6, 9, 11, 13, 15, 18, 28, 29, 30, 31], "random": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 28, 29, 30, 31], "random_forest_model": 10, "random_index": [13, 31], "random_indic": [1, 3], "random_st": [7, 8, 9, 10, 11], "randomforestclassifi": 10, "randomli": [1, 6, 9, 13, 14, 18, 30, 31], "rang": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 19, 22, 25, 28, 29, 30, 31], "rangl": [0, 6, 11, 25, 28, 29], "rangle_x": 25, "rank": [5, 29, 30], "rankdir": 4, "raphson": [1, 8, 13], "rapidli": [0, 31], "rare": [1, 13, 31], "raschka": [28, 29], "rasckha": 28, "rashcka": [30, 31], "rate": [1, 2, 3, 4, 8, 9, 10, 12, 13, 18, 30], "rather": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 25, 28, 29, 30], "ratio": [4, 7, 9, 10, 11], "rational": [0, 28], "ravel": [5, 6, 7, 8, 9, 10, 11, 13, 22], "raw": [3, 31], "rbf": [8, 11, 12], "rbf_kernel_svm_clf": 8, "rbf_pca": 11, "rc": 25, "rcond": [0, 28, 29], "rcparam": [1, 3, 7, 8, 9, 10, 25, 28], "re": [2, 4, 13, 15, 30], "reach": [1, 4, 5, 6, 9, 10, 12, 13, 14, 30, 31], "react": [], "read": [0, 2, 3, 4, 5, 6, 7, 8, 11, 12, 16, 17, 19, 20, 22, 23, 25, 27, 30], "read_csv": [0, 6, 7, 9], "read_fwf": [0, 28], "reader": [0, 6, 20, 22, 25, 28, 29, 31], "readi": [0, 1, 5, 6, 8, 10, 11, 12, 22, 28], "readili": 1, "readm": [15, 20], "readthedoc": 21, "real": [0, 1, 4, 7, 10, 11, 12, 16, 18, 19, 22, 29], "real_loss": 4, "real_output": 4, "realist": [8, 28], "realiti": 25, "realiz": [1, 12], "realli": [0, 1, 28], "rearrang": 13, "reason": [0, 1, 3, 4, 10, 13, 27, 28, 30, 31], "reassign": 1, "recal": [5, 6, 9, 10, 11, 12, 22, 25, 28, 29, 30, 31], "recast": 3, "receiv": [1, 3, 10, 12, 25], "recent": [0, 6, 13, 27, 31], "recept": [3, 12], "receptive_field": 3, "recip": [0, 6, 7, 22, 23, 28, 29], "reciproc": 5, "recogn": [0, 4, 5, 10, 28], "recognit": [0, 1, 3, 12, 27, 28], "recommen": 28, "recommend": [0, 2, 3, 4, 5, 6, 8, 13, 15, 19, 20, 21, 22, 23, 27, 30, 31], "reconsid": 9, "reconstruct": 11, "record": [10, 23, 24, 26, 28], "recreat": 15, "rectangl": [9, 13, 30], "rectangular": [5, 29, 30], "rectifi": [1, 3, 12], "recur": [0, 21, 28], "recurr": [0, 1, 21, 28], "recurs": [9, 21, 22, 28], "red": [0, 3, 4, 6, 8, 9, 31], "redefin": [0, 10, 28, 29, 30], "redefinit": 30, "redistribut": [], "reduc": [1, 3, 5, 6, 9, 10, 11, 13, 28, 30, 31], "reduct": [0, 10, 11, 21, 25, 28, 29], "reegress": 23, "ref": 20, "refer": [0, 1, 2, 3, 5, 6, 11, 12, 13, 14, 20, 22, 27, 28, 29, 30, 31], "referansestil": 20, "referenc": 2, "refin": 12, "refit": 6, "reflect": [0, 1, 4, 5, 23, 25, 28], "refresh": [21, 28], "refreshprogrammingskil": 28, "reg": [10, 11], "regard": [1, 9, 13], "regardless": [12, 16], "regexp": [], "regim": 31, "region": [3, 4, 6, 9, 12, 23, 31], "regist": [6, 25], "reglasso": [5, 30], "regr_1": [0, 9], "regr_2": [0, 9], "regr_3": [0, 9], "regress": [1, 8, 11, 12, 16, 20, 21, 22], "regressor": [0, 7, 10], "regret": [], "regridg": [0, 5, 6, 29, 30, 31], "regular": [0, 3, 4, 5, 6, 7, 9, 13, 17, 18, 26, 28, 29, 30, 31], "regularli": 15, "reilli": [0, 27, 28], "reinforc": [0, 8, 21, 28], "reiter": 1, "reitz": [], "reject": 7, "rel": [0, 4, 6, 7, 9, 12, 13, 25, 28, 29, 31], "relat": [0, 1, 3, 4, 5, 11, 13, 14, 19, 22, 25, 28, 29, 30], "relationship": [0, 4, 9, 18, 28], "relativeerror": [0, 28, 29], "releas": [1, 21, 28], "relev": [0, 1, 5, 7, 11, 21, 23, 25, 28, 30, 31], "reli": [0, 6, 8, 31], "reliabilti": 23, "reliabl": [7, 25], "relu": [3, 4, 28], "remain": [1, 2, 4, 6, 12, 22, 25, 29, 31], "remaind": 25, "reman": 2, "remark": 1, "rememb": [0, 8, 13, 20, 22, 23, 28, 31], "remind": [0, 5, 11, 13, 19, 22, 25], "remot": 15, "remov": [4, 5, 6, 18, 29, 30, 31], "renam": 15, "render": [0, 28, 29], "reorder": [5, 7, 29, 30], "reorgan": [0, 28], "repeat": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 14, 22, 23, 25, 28, 29, 30, 31], "repeated": 28, "repeatedli": [0, 6, 10, 13], "repet": 3, "repetit": [6, 28, 29], "rephras": [13, 30], "replac": [0, 1, 3, 4, 5, 6, 10, 12, 14, 21, 23, 28, 29, 30], "replica": 6, "repo": [15, 23], "report": [28, 31], "repositori": [4, 20, 23, 28], "reposotori": [], "repres": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 23, 25, 28, 29, 30, 31], "represent": [0, 1, 3, 6, 25, 28], "representd": 3, "reproduc": [0, 5, 6, 9, 12, 15, 16, 18, 20, 21, 25, 28, 29], "repuls": [0, 28], "request": [0, 13, 31], "requir": [0, 1, 3, 4, 5, 6, 8, 9, 11, 12, 13, 15, 17, 18, 19, 20, 22, 28, 29, 30, 31], "res1": 2, "res2": 2, "res3": 2, "res_analyt": 2, "res_analytical1": 2, "res_analytical2": 2, "res_analytical3": 2, "resaml": 6, "resampl": [0, 7, 10, 21, 28, 29], "rescal": [0, 11, 12, 31], "rescu": 5, "reseach": 6, "research": [0, 4, 13, 21, 27, 28, 31], "resembl": [6, 25], "reserv": [1, 5, 6, 25], "reshap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 22, 28, 29], "resid": 31, "residenti": [], "residu": [0, 5, 13, 28], "resiz": [5, 29, 30], "resnet": 31, "resort": 31, "resourc": [28, 31], "respect": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17, 18, 23, 25, 28, 29, 30, 31], "respond": 12, "respons": [0, 7, 9, 12, 28, 29], "rest": [0, 5, 18, 29, 30, 31], "restat": [0, 12, 28], "restor": 4, "restored_discrimin": 4, "restored_gener": 4, "restrict": [0, 3, 9, 12, 28], "result": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 28, 31], "retail": [], "retain": [5, 6, 29, 30, 31], "return": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 22, 25, 28, 29, 30, 31], "return_data": 14, "return_sequ": 4, "return_x_i": 9, "reus": [1, 3, 6, 19, 20, 23], "reveal": [0, 12, 28], "revers": [1, 22], "review": [21, 22], "revis": [], "revisit": 14, "revolut": 28, "reward": [0, 4, 28], "rewrit": [0, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 19, 22, 23, 25, 30, 31], "rewritten": [2, 6, 8, 10, 25], "rewrot": 13, "rf": 10, "rgb": 3, "rgoj5yh7evk": 21, "rh": 6, "rho": [0, 10, 13, 31], "rho_1": 10, "rho_2": 10, "rho_m": 10, "rich": [0, 28], "ride": 9, "rideclass": 9, "ridedata": 9, "ridg": [7, 11, 13, 20, 21, 28], "ridge_paramet": 17, "ridge_sk": 6, "ridgebeta": 30, "ridgetheta": 5, "right": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 19, 22, 23, 25, 28, 29, 30, 31], "right_sid": 2, "rightarrow": [0, 1, 5, 6, 8, 11, 12, 13, 25, 28, 29, 30, 31], "rigor": [0, 28, 29, 30], "ring": 6, "rise": [0, 28], "risk": [0, 13, 28, 30, 31], "rival": 4, "river": [], "rlm": 28, "rm": [25, 31], "rmse": [], "rmsporp": [13, 31], "rmsprop": [1, 3, 4, 13, 23], "rnd_clf": 10, "rng": 25, "rnn": [4, 12], "rnn1": 4, "rnn2": 4, "rnn_2layer": 4, "rnn_input": 4, "rnn_output": 4, "rnn_train": 4, "rntrick1": 25, "rntrick2": 25, "rntrick3": 25, "rntrick4": 25, "ro": [0, 13, 28, 30, 31], "robert": [19, 23, 27], "robust": [0, 28, 31], "robustscal": [0, 29, 31], "roc": [7, 10], "role": [0, 2, 5, 6, 8, 18, 21, 23, 28, 29, 30, 31], "roll": 6, "ronach": [], "room": [0, 26, 28], "root": [0, 5, 9, 13, 15, 25, 29, 30, 31], "root_directori": [], "rot": 28, "rotat": [1, 8, 9, 10], "rotation_matrix": 9, "roughli": [1, 3, 18], "round": [7, 9, 13], "routin": [13, 22, 28, 30], "row": [0, 1, 2, 5, 6, 9, 11, 16, 22, 28, 29, 30], "rr": [5, 29, 30], "rrr": [5, 29, 30], "rubric": [], "rudg": [], "rug": [13, 30, 31], "rule": [0, 1, 5, 6, 13, 23, 28, 29, 30], "run": [0, 1, 2, 4, 5, 6, 8, 9, 11, 13, 15, 20, 21, 23, 28, 29, 30, 31], "runtim": [1, 6, 14, 15], "rust": [0, 21, 22, 28], "rvert": 1, "rvert_2": 1, "s_": [3, 6], "s_1": 6, "s_i": [6, 7], "s_j": 6, "s_k": 6, "s_phenomenon": 23, "saddl": [13, 30, 31], "safeguard": [18, 31], "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 22, 23, 25, 28, 29, 30, 31], "said": [6, 9, 13, 30], "sake": [0, 5, 7, 11, 28, 29, 30], "sale": [0, 28], "sam": 28, "same": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 18, 20, 22, 23, 25, 28, 29, 30], "samm": 10, "sampl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 14, 18, 19, 21, 22, 23, 25, 28, 29, 31], "sample_vari": 14, "sampleexptvari": 25, "samwis": 28, "sastri": 11, "satisfactori": [0, 28], "satisfi": [1, 2, 3, 6, 8, 13, 22, 25, 30], "satur": [1, 6], "save": [0, 4, 6, 7, 9, 13, 20, 28, 31], "save_fig": [0, 6, 7, 9, 10, 28], "savefig": [0, 4, 6, 7, 9, 25, 28], "savetxt": 4, "saw": [5, 29], "scalabl": 10, "scalar": [2, 5, 6, 10, 29], "scale": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 22, 23, 26, 28, 30], "scale_mean": 4, "scale_std": 4, "scaler": [0, 7, 8, 9, 10, 11, 17, 23, 29], "scan": [5, 7], "scari": 5, "scatter": [0, 1, 6, 7, 8, 9, 14, 15, 17, 28, 29, 31], "scenario": [6, 13, 30, 31], "schedul": [13, 31], "scheme": [1, 13, 30, 31], "schrage": 25, "sch\u00f8yen": [6, 29, 31], "scienc": [0, 1, 10, 12, 13, 21, 24, 25, 26, 27, 30], "scientif": [0, 20, 21, 23, 28], "scientist": [0, 28], "scikit": [3, 5, 6, 8, 9, 10, 13, 15, 16, 20, 21, 22, 23, 27], "scikit_learn": 0, "scikitlearn": 28, "scikitplot": [7, 10], "scipi": [0, 3, 5, 6, 13, 21, 22, 23, 28, 29, 30], "scl": 6, "scm": 15, "score": [0, 1, 3, 6, 7, 9, 10, 11, 15, 16, 19, 23, 26, 28, 29, 31], "scores_kfold": 6, "scratch": [1, 13, 16], "script": [], "sdg": [13, 31], "sdv4f4s2sb8": [30, 31], "seaborn": [0, 1, 3, 6, 7, 28], "seamless": [0, 21, 23, 28], "search": [0, 1, 3, 5, 9, 13, 15, 28, 30, 31], "sebastian": 28, "sebastianraschka": 28, "sec": 6, "second": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 15, 16, 20, 21, 22, 25, 26, 28, 29, 30], "second_mo": 31, "second_term": 31, "secondari": 31, "secondeigvector": 11, "secondli": 12, "section": [4, 11, 16, 20, 22, 23, 25, 29, 31], "sector": 0, "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 18, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "seed": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 18, 20, 25, 28, 29, 30, 31], "seed_imag": 4, "seek": [1, 2, 8], "seem": [1, 3, 4, 31], "seemingli": [0, 28], "seen": [0, 1, 3, 5, 10, 12, 25], "segment": [13, 30], "seismic": 6, "seldomli": [0, 28], "select": [1, 5, 6, 8, 9, 10, 11, 15, 20, 23, 24, 25, 26, 27, 28, 29, 30, 31], "selevet": 15, "self": [1, 5, 29], "sell": 4, "semest": [7, 24], "semi": [8, 13, 30, 31], "semilogx": 6, "send": [5, 12, 13, 26, 28], "senior": [24, 26], "sens": [0, 4, 6, 8, 28], "sensibl": 3, "sensit": [0, 5, 6, 9, 13, 28, 29, 31], "sent": 2, "sentenc": [4, 12], "separ": [0, 1, 2, 4, 6, 8, 9, 12, 14, 18, 21, 23, 25, 28, 31], "septemb": [18, 23, 28], "sequenc": [3, 4, 7, 9, 10, 12, 13, 21, 22, 25, 28, 30], "sequenti": [1, 3, 4, 10, 12, 25], "seri": [0, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 22, 28, 29, 30], "serif": [7, 25, 28], "serv": [0, 1, 2, 3, 5, 7, 13, 27, 28, 29, 30, 31], "servic": 23, "session": [1, 15, 20, 23, 24, 26, 28], "set": [1, 4, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 18, 21, 22, 23, 25, 26, 31], "set_major_formatt": 6, "set_major_loc": 6, "set_tick": [1, 8], "set_ticklabel": 1, "set_titl": [0, 1, 2, 3, 7, 12, 14, 28], "set_xlabel": [0, 1, 2, 3, 7, 12, 28], "set_xlim": [7, 12], "set_xticklabel": 1, "set_ylabel": [0, 1, 2, 3, 7, 28], "set_ylim": [7, 12], "set_ytick": 7, "set_yticklabel": [1, 6], "set_zlim": 6, "seth": 4, "setminu": 6, "setosa": [8, 9], "setosa_or_versicolor": 8, "setp": 6, "setup": [1, 4, 6, 8, 21, 28, 29, 30], "sever": [0, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 21, 22, 23, 25, 28, 29, 30, 31], "sgd": [1, 3, 30], "sgd_clf": 8, "sgdclassifi": 8, "sgdreg": 13, "sgdregressor": 13, "sgn": [5, 29, 30], "shall": [], "shallow": [13, 31], "shape": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 22, 28, 29, 30, 31], "share": [1, 3, 15, 28], "shareabl": 15, "she": 7, "shibukawa": [], "shift": [1, 6, 12, 15, 18, 25, 29, 31], "ship": 3, "shire": 28, "short": [4, 5, 20, 23], "shortcom": [13, 30, 31], "shorten": 4, "shorter": 25, "shorthand": 28, "shortli": [22, 28], "should": [0, 2, 3, 5, 6, 8, 9, 11, 12, 15, 18, 19, 20, 22, 23, 25, 28, 29, 31], "show": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 22, 23, 25, 28, 29, 30, 31], "show_shap": 4, "shown": [0, 4, 5, 8, 12, 13, 22, 29, 30, 31], "shrink": [3, 5, 6, 8, 11, 29, 30, 31], "shrinkag": [5, 6, 29, 30], "shrunk": 11, "shuffl": [0, 1, 4, 6, 13, 29, 31], "side": [0, 2, 5, 8, 12, 13, 22, 23, 28, 30], "sigh": [21, 28], "sigma": [0, 1, 5, 6, 7, 10, 11, 12, 13, 19, 22, 23, 25, 28, 29, 30, 31], "sigma0": 25, "sigma1": 25, "sigma2": 25, "sigma_": [5, 22, 28, 29, 30], "sigma_0": [5, 29, 30], "sigma_1": [5, 29, 30], "sigma_2": [5, 29, 30], "sigma_fn": [7, 12], "sigma_i": [0, 5, 28, 29, 30], "sigma_j": [5, 29, 30], "sigma_m": [6, 25], "sigma_n": [11, 25], "sigma_t": 13, "sigma_x": 25, "sigmoid": [1, 2, 4, 7, 8, 10, 12], "sigmundson": [6, 29, 31], "sign": [1, 2, 7, 8, 10, 25, 26], "signal": [1, 3, 10, 12, 31], "signifi": 4, "signific": [1, 31], "significantli": [1, 13, 18, 25, 30, 31], "sim": [4, 5, 6, 13, 19, 25], "similar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 18, 21, 22, 23, 28, 30], "similarli": [0, 1, 3, 5, 8, 10, 13, 25, 28, 29, 30, 31], "simpl": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 14, 16, 17, 21, 22, 25], "simplepredict": 10, "simpler": [0, 1, 5, 6, 7, 13, 16, 21, 23, 28, 30, 31], "simplernn": 4, "simplest": [0, 1, 3, 4, 9, 10, 12, 14, 23, 28], "simpletre": 10, "simpli": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 21, 22, 23, 25, 28, 29, 30, 31], "simplic": [2, 5, 6, 7, 8, 9, 10, 11, 12, 14, 29, 30, 31], "simplicti": [5, 29, 30], "simplifi": [0, 6, 9, 18, 21, 23, 28, 29, 31], "simplist": [3, 6, 25], "simul": [6, 18, 31], "simultan": [6, 31], "sin": [0, 1, 2, 3, 4, 9, 12, 13, 22, 28], "sinc": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 16, 18, 22, 23, 25, 27, 28, 29, 30, 31], "sine": [3, 12], "singl": [0, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 18, 19, 22, 25, 28, 29, 30, 31], "singular": [0, 6, 13, 22, 28], "sinusoid": 3, "site": [0, 23, 24, 29], "situat": [0, 4, 5, 7, 13, 25, 28, 29, 30, 31], "six": [3, 25], "size": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 18, 20, 22, 23, 25, 28], "sizesp": 31, "sketch": 10, "ski": 9, "skill": 0, "skip": 11, "skl": [0, 6, 28, 29, 31], "sklearn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 19, 20, 28, 29, 30, 31], "skplt": [7, 10], "sl": [6, 29, 31], "slack": 8, "slender": [], "slice": [2, 22, 28], "slide": [0, 3, 16, 23, 25, 28, 29, 30], "slight": [6, 13], "slightli": [1, 2, 3, 5, 6, 7, 10, 25, 29, 30], "slope": [8, 11, 12], "slow": [0, 2, 8, 13, 18, 29, 30, 31], "slower": [5, 22, 28, 29, 30, 31], "slowest": 22, "slowli": [12, 31], "slp": 1, "small": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 18, 21, 22, 25, 28, 29, 30, 31], "smaller": [0, 1, 2, 5, 6, 8, 9, 11, 13, 25, 28, 29, 30, 31], "smallest": [0, 4, 14, 28], "smallest_row_index": 14, "smodin": [], "smooth": [0, 3, 6, 13, 23, 28, 30, 31], "smoother": 31, "sn": [0, 1, 3, 6, 7, 28], "sne": 11, "so": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31], "soar": 6, "social": 0, "soft": [1, 7, 10, 12], "soften": 8, "softmax": [3, 7], "softwar": [0, 8, 21, 22], "sokogskriv": 20, "sol": 8, "sole": [0, 6, 28], "solid": [0, 7], "solut": [0, 1, 2, 3, 5, 6, 8, 10, 11, 13, 18, 22, 23, 25, 28, 29, 30, 31], "solution_ev": 31, "soluton": 2, "solv": [0, 1, 3, 5, 6, 8, 10, 11, 12, 13, 16, 22, 23, 28, 29], "solve_expdec": 2, "solve_ode_deep_neural_network": 2, "solve_ode_neural_network": 2, "solve_pde_deep_neural_network": 2, "solveod": 2, "solveode_popul": 2, "solver": [2, 7, 8, 9, 10, 22, 28], "some": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 23, 25, 28, 31], "some_model": [6, 29, 31], "somehow": 4, "someon": 16, "someth": [0, 1, 3, 4, 7, 9, 11, 15, 19, 20, 23, 25, 28, 29], "sometim": [0, 1, 11, 12, 13, 14, 19, 29, 31], "soon": [22, 26, 29], "sophist": [0, 28], "sopt": 13, "sort": [5, 6, 9, 11, 25], "sound": [3, 5], "sourc": [0, 1, 3, 6, 21, 22, 23, 25, 28, 31], "space": [0, 1, 4, 5, 8, 9, 11, 12, 13, 14, 25, 29, 30, 31], "span": [0, 3, 5, 9, 11, 22, 28, 29, 30], "spare": 1, "spars": [3, 6, 18, 22, 28, 31], "sparse_mtx": [22, 28], "sparsecategoricalcrossentropi": 3, "sparsiti": [10, 18], "spatial": [1, 2, 3, 12], "speak": 25, "special": [6, 7, 10, 12, 13, 22, 25, 28, 29, 30, 31], "specif": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 15, 16, 21, 22, 23, 25, 27, 28, 29, 30], "specifi": [0, 3, 5, 6, 7, 9, 11, 13, 14, 25, 28, 30, 31], "specifici": [0, 10, 28], "spectacular": 3, "spectral": 1, "speech": [0, 1, 3, 4, 12], "speed": [1, 2, 4, 13], "spend": [16, 25, 31], "spent": 23, "sphere": [0, 29, 31], "sphinx": [], "sphinx_book_them": [], "sphinxcontrib": [], "spike": 31, "spin": 6, "spite": 0, "spitzer": [], "spline": 8, "split": [1, 3, 4, 5, 6, 8, 9, 10, 11, 14, 16, 17, 20, 23, 25, 28, 30, 31], "splite": 0, "splitter": [1, 10], "spoiler": [], "spontan": 25, "spot": 3, "spread": [0, 11, 25, 28, 29], "springer": [19, 23, 27, 28], "spuriou": [13, 31], "sqquar": 30, "sqrsignal": 3, "sqrt": [3, 4, 5, 6, 8, 10, 11, 13, 25, 29, 30, 31], "squar": [1, 2, 3, 4, 7, 8, 9, 11, 13, 14, 15, 17, 18, 21, 22, 25], "squarederror": 10, "squaredeuclidean": 14, "squash": 12, "src": [], "srtm": 6, "srtm_data_norway_1": 6, "stabil": [5, 23, 31], "stabl": [0, 4, 5, 6, 9, 16, 20, 21, 23, 28, 29, 30, 31], "stack": [3, 4], "stage": [5, 13, 15, 23, 31], "stagnat": 31, "stai": [0, 2, 4, 5, 11, 28, 29, 31], "stand": [0, 5, 9, 12, 28, 29, 30], "standard": [0, 1, 4, 5, 6, 7, 8, 10, 12, 17, 18, 19, 22, 23, 25, 28, 30, 31], "standardscal": [0, 6, 7, 8, 9, 10, 11, 17, 29, 31], "standpoint": 31, "stanford": [13, 30], "start": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 22, 25, 26, 28, 29, 30, 31], "start_tim": 14, "starter": [], "stat": 6, "state": [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 21, 25, 28, 29, 30], "statement": [0, 7, 22, 28], "static": [], "stationari": [30, 31], "statist": [0, 1, 3, 4, 7, 9, 10, 11, 12, 13, 14, 19, 22, 23, 27, 29, 30, 31], "statu": [0, 7, 15, 28], "stavang": 6, "stb": [], "std": [0, 4, 6, 18, 28, 29, 31], "steep": [13, 30, 31], "steepest": 31, "stefan": [], "step": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 22, 23, 28, 30], "step_fn": [7, 12], "step_length": [13, 31], "step_siz": 31, "steps_list": 9, "stereo": 3, "sticki": [], "still": [0, 2, 3, 5, 6, 11, 13, 25, 29, 30, 31], "stimuli": 12, "stk": [27, 28], "stk2100": [27, 28], "stk3155": [15, 23, 24, 26], "stk4021": [27, 28], "stk4051": [27, 28], "stk4155": [24, 26], "stk5000": 27, "stochast": [0, 1, 5, 6, 8, 11, 12, 30], "stock": 4, "stoke": 12, "stone": [0, 7], "stop": [1, 4, 9, 13, 14, 18, 30], "storag": [5, 29, 30], "store": [0, 1, 2, 3, 6, 11, 13, 25, 28, 31], "storehaug": [26, 28], "str": [1, 3, 4], "straight": [0, 6, 8, 13, 28, 30], "straightforward": [0, 2, 3, 5, 6, 8, 9, 10, 13, 22, 28, 29, 30], "strategi": [0, 1, 9, 28], "stratifi": 6, "stream": 31, "strength": [0, 5, 14, 29, 30], "stretch": 11, "strict": [8, 13, 30], "strictli": [8, 13, 30], "stride": [4, 22], "strike": 6, "string": 1, "stroke": 7, "strong": [3, 6, 9, 10, 12, 22, 25, 31], "strongli": [0, 8, 15, 20, 21, 22], "stronli": [], "structur": [0, 1, 2, 3, 6, 9, 10, 12, 21, 28], "stuck": [1, 13, 30, 31], "student": [0, 15, 23, 24, 26, 27, 28], "studi": [0, 3, 4, 5, 6, 7, 8, 11, 12, 13, 21, 23, 27, 28, 29, 30, 31], "studier": 27, "style": [7, 9, 20, 22, 28], "stylesheet": [], "st\u00f8land": 26, "sub": [9, 12, 31], "subdivid": [0, 22, 28], "subfield": 0, "subgradi": 31, "subject": [6, 8, 25], "sublicens": [], "sublinear": 31, "submit": 28, "subplot": [0, 1, 3, 4, 6, 7, 8, 9, 10, 14, 28], "subplots_adjust": [8, 25], "subprogram": [22, 28], "subproject": [], "subract": [0, 29], "subroutin": [0, 28], "subscript": 1, "subsequ": [1, 4, 5, 6, 12, 22, 25, 29, 30], "subset": [1, 6, 9, 12, 13, 21, 28, 30, 31], "subspac": [0, 8, 11, 29], "substanti": [9, 10, 31], "substep": 11, "substitut": [3, 6, 12, 16, 22], "subsubset": 9, "subtask": 6, "subtl": 1, "subtract": [0, 4, 5, 6, 11, 13, 18, 19, 22, 23, 25, 29, 31], "subtre": 9, "succeed": [0, 4, 28], "success": [3, 7, 9, 13, 25], "successfulli": [4, 9], "succinctli": 31, "sudo": [0, 21, 23, 28], "suffer": [0, 1, 2, 5, 10, 28, 29, 30], "suffici": [1, 6, 8, 11, 13, 30], "suggest": [1, 13, 23, 27, 30, 31], "suit": [8, 12], "suitabl": [0, 15, 19, 25, 29, 31], "sum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 19, 22, 25, 28, 29, 30, 31], "sum_": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 19, 22, 23, 25, 28, 29, 30, 31], "sum_i": [0, 2, 5, 6, 8, 13, 19, 23, 29, 30, 31], "sum_j": [6, 18, 31], "sum_ja_": 0, "sum_k": [6, 8, 12, 22], "sum_logist": 13, "sum_m": 3, "sum_n": 3, "sum_nx_": 3, "summar": [5, 6, 9], "summari": [1, 3, 4, 10, 24, 30, 31], "summat": [0, 3, 16, 29, 30], "sunni": 9, "super": [5, 29, 30, 31], "superfici": 3, "superscript": [1, 12], "supervis": [0, 5, 6, 7, 9, 12, 21, 28, 29, 30], "supplement": [7, 23], "suppli": [], "support": [0, 1, 9, 10, 11, 13, 20, 21, 28, 29, 31], "suppos": [0, 5, 6, 7, 8, 10, 11, 12, 13, 22, 28, 29, 30, 31], "suppress": [5, 13, 30], "sure": [0, 1, 4, 6, 16, 20, 23], "surf": 6, "surfac": [0, 6, 28, 31], "surpass": 6, "surpris": [0, 28], "surround": [3, 21], "survei": [0, 5, 6, 28, 29], "svc": [8, 9, 10], "svd": [0, 6, 11, 28], "svdinv": 5, "svm": [8, 9, 10, 11], "svm_clf": [8, 10], "swath": [5, 29, 30], "switch": 0, "sy": [13, 30, 31], "symbol": [1, 5, 11, 13, 21, 25, 28, 29, 30], "symmeteri": 1, "symmetr": [0, 5, 8, 11, 12, 13, 22, 28, 29], "symmetri": 6, "sympi": [0, 21, 23, 28], "synonim": 25, "syntax": 13, "system": [0, 1, 3, 4, 6, 7, 9, 10, 12, 13, 15, 21, 22, 23, 28, 30, 31], "systemat": [4, 6], "t": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 26, 28, 30, 31], "t0": [3, 6, 13, 31], "t1": [2, 13, 31], "t2": 2, "t3": 2, "t_": 2, "t_0": [2, 9, 13, 31], "t_1": [13, 31], "t_b": 10, "t_i": [1, 2, 5, 12, 29, 30], "t_j": 12, "t_k": 9, "tabl": [9, 23, 25, 26, 28], "tabul": [0, 28], "tabular": 28, "tackl": 4, "tag": [2, 3, 4, 5, 6, 7, 12, 13, 14, 22, 25, 29, 30], "taht": [0, 28], "tail": 25, "tailor": [2, 8, 11, 28], "taiwan": [0, 28], "take": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 19, 21, 22, 25, 28, 29, 30, 31], "taken": [0, 1, 3, 6, 10, 13, 22], "tan": 3, "tangent": [1, 4, 12, 13, 30], "tanh": [1, 4, 7, 8, 12], "target": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 18, 19, 28, 29, 30, 31], "target_nam": 9, "task": [0, 1, 3, 6, 9, 11, 12, 14, 23, 28, 31], "tau": [3, 5, 25], "taught": 28, "tax": [], "taylor": [2, 13, 30], "taylornr": [13, 30], "tc": 8, "teach": [15, 24, 28], "team": 1, "teaser": 0, "technic": [0, 5, 6, 13, 23, 30, 31], "techniqu": [0, 1, 8, 10, 13, 21, 25, 27, 28, 29, 31], "technologi": [0, 1], "tell": [0, 4, 6, 10, 11, 13, 16, 25, 31], "temp": 1, "temp1": 1, "temp2": 1, "temperatur": [0, 9, 28], "templat": [18, 20], "temporarili": 1, "ten": [3, 28], "tend": [3, 5, 6, 8, 9, 10, 12, 13, 14, 29, 31], "tendenc": [0, 28], "tension": 6, "tensor": 3, "tensorflow": [0, 2, 4, 8, 14, 21, 22, 23, 27, 28, 29], "term": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 23, 25, 28, 29, 30, 31], "term1": [5, 6, 11], "term2": [5, 6, 11], "term3": [5, 6, 11], "term4": [5, 6, 11], "termin": [0, 4, 5, 9, 10, 13, 15, 29, 30, 31], "terminarl": 15, "terrain": 6, "terrain1": 6, "test": [3, 4, 5, 6, 7, 8, 9, 10, 13, 16, 20, 22, 23, 25, 28, 30, 31], "test_acc": 3, "test_accuraci": [1, 3], "test_error": 6, "test_imag": [3, 4], "test_ind": 6, "test_input": 4, "test_label": [3, 4], "test_loss": 3, "test_pr": 1, "test_predict": 1, "test_rnn": 4, "test_scor": [7, 10], "test_siz": [0, 1, 3, 5, 6, 10, 15, 17, 29, 30, 31], "test_split": 9, "testerror": [0, 6, 29], "testi": 4, "testpredict": 4, "testx": 4, "tex": [], "text": [0, 1, 2, 4, 5, 8, 9, 11, 13, 15, 18, 20, 22, 25, 27, 29, 30, 31], "textbf": [], "textbook": [16, 23, 29, 30], "textual": 9, "textur": 1, "tf": [1, 3, 4, 13, 14, 30], "th": [0, 1, 2, 5, 6, 7, 9, 12, 13, 14, 22, 23, 25, 28, 29, 31], "than": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 17, 21, 25, 28, 29, 31], "thank": [4, 6, 29, 31], "theano": [1, 21, 28], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 18, 20, 22, 23, 25, 28, 29, 30, 31], "them": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 13, 18, 19, 22, 23, 28, 29], "theme": [0, 15, 28], "themselv": [0, 23, 25, 28, 31], "thenc": 6, "theorem": [2, 6, 7, 29, 30], "theoret": [0, 4, 10], "theori": [0, 1, 3, 8, 9, 12, 13, 19, 21, 23, 27, 28, 31], "thereaft": [0, 5, 6, 11, 12, 22, 23, 28], "therebi": [0, 5, 7, 11, 23, 28, 29, 30], "therefor": [0, 1, 2, 3, 4, 6, 7, 8, 11, 13, 19, 25, 28, 29, 30, 31], "therein": 11, "thereof": [0, 6, 13, 28, 31], "theta": [0, 1, 4, 5, 6, 7, 13, 16, 23, 25, 28, 29, 30, 31], "theta1": 31, "theta2": 31, "theta_": [0, 1, 6, 7, 13, 28, 29, 30, 31], "theta_0": [0, 5, 6, 7, 16, 28, 29, 30, 31], "theta_0x_": [0, 28, 29], "theta_1": [0, 5, 6, 7, 28, 29, 30, 31], "theta_1x_": [0, 28, 29], "theta_1x_0": [0, 28], "theta_1x_1": [0, 7, 28], "theta_1x_2": [0, 28], "theta_1x_i": [7, 29, 30, 31], "theta_2": [0, 28, 29], "theta_2x_": [0, 28, 29], "theta_2x_0": [0, 28], "theta_2x_1": [0, 28], "theta_2x_2": [0, 7, 28], "theta_2x_i": 29, "theta_3x_i": 29, "theta_4x_i": 29, "theta_closed_form": 18, "theta_closed_formol": 18, "theta_closed_formridg": 18, "theta_gdol": 18, "theta_gdridg": 18, "theta_i": [0, 1, 5, 28, 29, 30], "theta_j": [0, 5, 6, 18, 28, 29, 31], "theta_k": [30, 31], "theta_linreg": [13, 30, 31], "theta_ol": 18, "theta_p": 7, "theta_px_p": 7, "theta_ridg": 18, "theta_t": [13, 31], "theta_tru": 18, "thetaith": 31, "thetavalu": 5, "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29, 30, 31], "thing": [0, 1, 2, 4, 5, 7, 9, 15, 16, 18, 25, 28], "think": [0, 1, 3, 4, 6, 9, 12, 13, 14, 25, 28, 29, 30, 31], "third": [0, 3, 6, 13, 26, 28, 30, 31], "thirti": 7, "thorughout": 28, "those": [0, 3, 5, 6, 8, 9, 10, 11, 22, 23, 28, 29, 30, 31], "though": [1, 2, 3, 4, 13, 16, 17, 19, 22, 25, 31], "thought": [6, 14, 23, 25], "thousand": [0, 1, 23, 29, 31], "three": [0, 1, 3, 5, 6, 8, 9, 12, 22, 23, 24, 25, 26, 28, 29, 30], "threshold": [1, 3, 9, 10, 11, 12, 13, 31], "through": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12, 13, 14, 15, 21, 22, 23, 25, 28, 29, 30, 31], "throughout": [0, 4, 5, 14, 15, 21, 22, 25, 28], "throw": [3, 6, 25], "thu": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 26, 28, 29, 30, 31], "thumb": [0, 6, 23, 29], "thursdai": [], "tibshirani": [6, 19, 23, 27, 28], "tick_param": 6, "ticker": [6, 13, 25, 30, 31], "tif": 6, "tight_layout": [1, 7], "tightli": 11, "tild": [0, 5, 6, 7, 11, 19, 23, 25, 28, 29, 30, 31], "till": [0, 4, 7, 8, 9, 10, 12, 22, 28, 29], "time": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 25, 28, 29, 30], "timeit": 4, "timer": 4, "tini": [1, 31], "tip": 3, "titl": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 15, 20, 25, 28, 30, 31], "tm": [], "tmp": 13, "tn": [2, 3, 7], "to_categor": [1, 3, 4], "to_categorical_numpi": 1, "to_numer": [0, 6, 28], "todai": 3, "togeth": [0, 3, 6, 8, 11, 13, 21, 28], "toi": 14, "token": [], "told": 13, "toler": [2, 14], "tolist": 4, "tomographi": 12, "too": [0, 2, 4, 5, 6, 9, 11, 13, 17, 18, 25, 27, 29, 30, 31], "took": [8, 28], "tool": [0, 1, 3, 6, 13, 15, 21, 29], "toolbox": 8, "top": [0, 3, 5, 6, 9, 10, 19, 21, 28], "topic": [0, 5, 6, 7, 8, 21, 23, 29, 30], "topolog": [3, 12], "topologi": [1, 12], "torkjellsdatt": [26, 28], "tort": [], "toss": [10, 25], "total": [0, 1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 13, 14, 22, 25, 26, 28, 29, 30, 31], "total_loss": 4, "totalclustervari": 14, "totalscatt": 14, "toward": [1, 2, 7, 12, 13, 15, 30], "towardsdatasci": 31, "town": [], "tp": [4, 7], "tpng": 9, "tpu": [13, 21, 28], "tqdm": 6, "tr": [], "track": [3, 13, 14, 15, 22, 29, 30, 31], "tract": [], "tractabl": [0, 28, 29], "trade": [5, 9, 20, 31], "tradeoff": [0, 5, 19, 23, 28, 29, 30], "tradit": [0, 1, 4, 6, 28], "train": [2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 16, 17, 20, 23, 30, 31], "train_accuraci": [0, 1, 3, 28], "train_dataset": 4, "train_end": [0, 1, 29], "train_error": 6, "train_imag": [3, 4], "train_ind": 6, "train_label": [3, 4], "train_pr": 1, "train_siz": [0, 1, 3, 29], "train_step": 4, "train_test_split": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "train_test_split_numpi": [0, 1, 29], "trainable_vari": 4, "trained_model": [6, 29, 31], "trainerror": [0, 29], "traini": 4, "training_checkpoint": 4, "training_dataset": 4, "training_gradi": [13, 31], "trainingerror": 6, "trainpredict": 4, "trainscor": 4, "trainx": 4, "trait": [0, 28], "trajectori": [4, 31], "transfer": [9, 28], "transform": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 21, 22, 28, 29, 30, 31], "transit": [6, 12], "translat": [1, 4, 6, 10, 28, 29, 31], "transpos": [1, 5, 11, 22, 29, 30], "travers": [0, 5], "treat": [0, 1, 3, 6, 12, 13, 18, 25, 28, 29, 30, 31], "tree": [0, 1, 21, 28], "tree_clf": [9, 10], "tree_clf_": 9, "tree_clf_sr": 9, "tree_reg": 9, "tree_reg1": 9, "tree_reg2": 9, "trend": 25, "treue": 7, "trevor": [19, 23, 27], "tri": [2, 3, 4, 9, 13, 16, 31], "triain": 0, "trial": [0, 2, 4, 6, 13, 25, 28, 30, 31], "triangl": [13, 30], "triangular": 22, "trick": [3, 4, 8, 11, 13, 25, 31], "trickier": 25, "tridiagon": 22, "trillion": 21, "trim": [], "trivial": [0, 1, 5, 11, 25, 28, 30], "troffa": [], "troubl": [0, 8, 12, 15, 29, 31], "truck": 3, "true": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "true_beta": 29, "true_fun": 6, "true_theta": [6, 31], "truli": 28, "try": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 18, 21, 22, 23, 25, 28, 29, 30, 31], "tr\u00f6ger": [], "tucker": 8, "tuesdai": [26, 28], "tumor": [7, 9], "tumour": 7, "tunabl": 1, "tune": [4, 9, 13, 22, 28, 31], "turn": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 25, 28, 29, 30, 31], "tutori": [1, 4], "tv": 2, "tveito": 2, "tweak": [1, 4, 10, 25], "twice": [13, 30], "twist": 11, "two": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 17, 22, 23, 24, 25, 27, 28, 29, 30, 31], "tx": [13, 30, 31], "tx_1": [13, 30], "txt": [4, 15, 20], "ty": [13, 30], "type": [0, 1, 3, 6, 8, 10, 13, 22, 25, 29, 30, 31], "typeset": 20, "typic": [0, 1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 20, 25, 28, 29, 30, 31], "typo": 23, "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 22, 23, 25, 27, 28, 29, 30, 31], "u_": 22, "u_i": 12, "u_m": 10, "ua": [0, 28], "ubuntu": [0, 21, 23, 28], "uci": 23, "uio": [15, 23, 26, 27], "un": 14, "unabl": 15, "unari": [22, 28], "unbalanc": [6, 9], "unbias": [0, 5, 6, 28], "uncent": [6, 29, 31], "uncertainti": [0, 5, 28], "uncertitud": 25, "unchang": [1, 3], "uncorrel": [10, 25], "undefin": [5, 29, 30], "under": [0, 1, 5, 6, 10, 13, 21, 23, 28, 29, 30, 31], "underdetermin": [0, 28], "underfit": [1, 6], "underflowproblem": 5, "undergo": 5, "undergradu": [24, 26], "underli": [0, 1, 9, 13, 18, 25, 28, 31], "underlin": [], "underscor": [], "underset": [4, 14], "understand": [0, 1, 3, 5, 6, 10, 13, 14, 15, 19, 20, 21, 28, 29, 30, 31], "understood": [8, 13], "undesir": 8, "undetermin": [5, 8], "undo": 4, "unexpect": 6, "unexpected": 25, "unexplain": 18, "unfair": [6, 29], "unfortun": [1, 8, 9, 10], "unicode_liter": [8, 9], "uniform": [0, 1, 5, 6, 11, 13, 23, 25, 28, 30, 31], "uniformli": [13, 25, 30, 31], "unifrompdf": 25, "unimport": [13, 30], "union": [5, 6], "uniqu": [0, 2, 6, 13, 14, 22, 28], "unique_cluster_label": 14, "unit": [0, 1, 3, 4, 5, 10, 12, 18, 25, 28, 29, 30, 31], "unitari": [5, 6, 22, 29, 30], "unitarili": [22, 28], "uniti": 25, "univari": 25, "univers": [0, 1, 2, 13, 21, 23, 24, 26, 28, 29, 30, 31], "unix": 1, "unknow": [0, 22, 28], "unknown": [0, 1, 3, 4, 5, 6, 8, 10, 13, 22, 23, 28, 29, 30, 31], "unknowwn": 12, "unlabel": 1, "unless": [0, 3, 6, 11, 13, 23, 28, 30], "unlik": [1, 3, 8, 13, 30, 31], "unnecessarili": 9, "unord": 3, "unpublish": 31, "unravel": 1, "unrol": [3, 11], "unscal": 19, "unseen": [0, 7, 9, 15], "unstabl": 1, "unsupervis": [0, 1, 4, 12, 21, 28], "unsymmetr": [22, 28], "until": [1, 2, 4, 9, 12, 13, 14, 30, 31], "untouch": 0, "unusu": 12, "up": [1, 3, 4, 5, 6, 8, 10, 11, 13, 14, 16, 18, 19, 20, 21, 22, 23, 25, 26, 31], "updat": [1, 2, 10, 12, 13, 14, 15, 18], "uploa": 28, "upload": [15, 20, 21, 23, 27], "upon": [0, 1, 6, 7, 11, 22], "upper": [0, 8, 9, 16, 22, 29], "uppercas": [22, 28], "upsampl": 4, "upscal": 4, "url": [28, 29], "us": [4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 17, 20, 22, 25, 27], "usag": [0, 8, 21, 28, 29], "usd": [], "usd10000": [], "use_bia": 4, "usecol": [0, 28], "useless": 1, "user": [0, 1, 2, 4, 6, 7, 15, 21, 22, 23, 28, 29], "usernam": [15, 23], "usetex": 25, "usg": 6, "usr": 25, "usual": [0, 3, 4, 7, 12, 13, 14, 28, 31], "ut": 5, "utf": [], "util": [1, 3, 4, 6, 7, 10, 14, 19, 28], "ux": 22, "v": [2, 4, 5, 6, 11, 13, 15, 21, 29, 30], "v0": 25, "v1": 25, "v2": 25, "v5": [], "v_": 31, "v_0": [11, 31], "v_t": 31, "va": 1, "vahid": 28, "val": 13, "val_accuraci": 3, "val_loss": 4, "vale": 2, "valid": [0, 1, 4, 7, 9, 10, 13, 21, 25, 28, 29, 31], "validation_data": 3, "validation_split": 4, "valu": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 20, 21, 22, 23, 28, 31], "valuat": 9, "valy": 4, "van": [0, 19, 23, 28, 29, 30, 31], "vandenbergh": [8, 13, 30], "vandermond": [0, 28], "vanilla": [0, 6, 11, 14, 29, 31], "vanish": [1, 4, 13, 25, 30], "var": [5, 6, 10, 11, 19, 23, 25, 29], "var_x": 25, "varabl": 8, "varepsilon": [5, 6, 19], "varepsilon_": [5, 6], "varepsilon_i": [5, 6], "vari": [0, 1, 3, 5, 6, 10, 28], "variabl": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 14, 22, 28, 29, 31], "varianc": [0, 1, 5, 7, 9, 10, 11, 13, 14, 18, 20, 21, 22, 25, 28, 29, 30, 31], "variance_i": [5, 11, 29], "variance_x": [5, 11, 29], "variant": [0, 1, 6, 8, 12, 13, 28, 29, 30, 31], "variat": [3, 4, 11, 28], "varieti": [0, 3, 12, 21, 23, 28], "variou": [1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 19, 20, 21, 22, 23, 25, 28, 29, 30, 31], "varydimens": 4, "vast": 31, "vastli": 3, "vaue": 1, "vault": 0, "vdot": [2, 13, 30, 31], "ve": [23, 31], "vec": 6, "vector": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 17, 18, 21, 30, 31], "vector_mean": 14, "ventur": [0, 8, 21, 28], "venv": 15, "verbos": [1, 3, 4], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 23, 25, 27, 28, 29, 30, 31], "verifi": [3, 11, 22, 28], "versatil": [8, 28], "versicolor": [8, 9], "version": [0, 3, 10, 13, 14, 15, 21, 22, 23, 25, 28], "versu": [1, 31], "vert": [0, 1, 5, 6, 7, 8, 9, 11, 13, 16, 17, 28, 29, 30, 31], "vert_1": [5, 6, 29, 30, 31], "vert_2": [5, 6, 11, 17, 29, 30, 31], "via": [0, 5, 6, 7, 8, 9, 10, 11, 12, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31], "vidal": 11, "video": [0, 1, 12, 21, 24, 26, 28, 29, 30], "view": [1, 3, 5, 6, 12, 13, 25, 27, 28, 30, 31], "violat": 8, "virginica": 9, "viridi": [0, 1, 2, 3, 28], "virtanen": [], "virtual": [1, 31], "viscos": 13, "viscou": 13, "visibl": 15, "vision": [0, 3], "visit": 31, "visual": [0, 3, 11, 12, 18, 21, 28, 29], "visualis": 1, "visualstudio": [15, 16, 19], "viz": [6, 8, 25], "vmap": 13, "vmax": [1, 6], "vmh0zpt0tli": 31, "vmin": [1, 6], "voic": 3, "volatil": 31, "volum": [0, 3, 28], "vote": [10, 28], "voting_clf": 10, "votingclassifi": 10, "votingsimpl": 10, "vscode": [], "vstack": [5, 11, 22, 25, 28, 29], "vt": [5, 29, 30], "w": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 22, 25, 28, 29, 30, 31], "w1": 8, "w2": [8, 11], "w3": 8, "w_": [1, 12], "w_1": [8, 22], "w_1x_": 8, "w_1x_1": 8, "w_2": [8, 22], "w_2x_": 8, "w_2x_2": 8, "w_3": 22, "w_4": 22, "w_hidden": 2, "w_i": [1, 2, 10], "w_ix_i": 12, "w_j": 22, "w_m": 22, "w_output": 2, "w_px_": 8, "w_px_p": 8, "w_t": [], "wa": [1, 3, 4, 5, 6, 7, 10, 11, 12, 14, 17, 22, 28, 29, 31], "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 19, 22, 25, 28, 29, 30, 31], "walk": 9, "walker": 25, "wall": 31, "walt": [], "wang": [0, 28], "want": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20, 21, 23, 25, 28, 29, 30, 31], "warn": 4, "warrant": 6, "warranti": [], "wast": [3, 31], "watch": [21, 30, 31], "wave": 3, "wavelet": 8, "wcag": [], "we": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 29, 30], "weak": [9, 10, 14], "weaker": 31, "weather": [1, 12], "web": [21, 24, 26, 28], "webpag": 28, "websit": [6, 22, 23, 24, 28], "wedg": [8, 25], "wednesdai": [26, 28], "wee": 11, "week": [0, 5, 6, 7, 23, 24, 26], "weekli": [15, 16, 21, 23, 24, 26, 27, 28], "weight": [1, 2, 3, 6, 7, 9, 10, 12, 13, 18, 25, 31], "weigth": 2, "welcom": [8, 15, 21], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 20, 21, 22, 23, 25, 27, 28, 29, 30, 31], "went": 8, "were": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 25, 28, 31], "wessel": [0, 19, 23, 28, 29, 30, 31], "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 25, 31], "whatev": 3, "when": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 22, 23, 25, 28, 29, 30], "whenev": [13, 15, 25, 31], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31], "wherea": [6, 25, 31], "wherefrom": 23, "wherein": [1, 12], "whether": [0, 3, 5, 7, 9, 23, 25, 28], "which": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30], "whichev": [1, 3], "while": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 19, 20, 25, 28, 29, 30, 31], "white": 9, "whiteboad": 31, "whiteboard": [29, 30, 31], "who": [0, 15], "whole": [1, 3, 4, 5, 9, 11, 13, 31], "whom": [], "whose": [0, 6, 10, 25, 29], "whow": [11, 29], "why": [0, 1, 3, 6, 13, 15, 16, 17, 19, 23, 29, 30], "wide": [0, 1, 3, 6, 7, 12, 21, 22, 23, 28], "widehat": 6, "width": [0, 3, 8, 9, 28], "wieringen": [0, 19, 23, 28, 29, 30, 31], "wiki": 23, "wikipedia": 23, "win": [10, 31], "wind": 9, "window": [], "wing": [26, 28], "winther": 2, "wiothout": 6, "wiscons": 7, "wisconsin": 10, "wisdom": [6, 29, 31], "wise": [1, 5, 12, 13, 29, 30, 31], "wish": [0, 2, 5, 7, 8, 11, 13, 14, 18, 22, 23, 28, 29, 30, 31], "with_std": [0, 29], "wither": 6, "within": [0, 2, 3, 4, 7, 9, 12, 13, 14, 25, 27, 28, 30], "withinclust": 14, "without": [0, 1, 5, 6, 8, 9, 11, 12, 13, 15, 18, 23, 28, 29, 30, 31], "won": [0, 15, 28], "wonder": 8, "word": [0, 1, 3, 4, 5, 6, 7, 14, 25, 28, 29, 30, 31], "work": [0, 1, 4, 6, 7, 8, 9, 13, 15, 16, 18, 19, 20, 21, 23, 24, 25, 26, 28, 29, 31], "workabl": 31, "workaround": [], "workhors": 31, "workload": 31, "workshop": 28, "world": [0, 8, 16, 29], "worldwid": [0, 28], "worri": 15, "wors": [0, 1, 3, 4, 6, 28, 31], "worth": [9, 19], "worthi": 23, "would": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 18, 20, 22, 23, 25, 28, 29, 30, 31], "wrap": [6, 22, 28], "write": [0, 1, 2, 3, 5, 6, 7, 8, 12, 13, 15, 16, 18, 22, 28, 29, 31], "written": [0, 2, 3, 5, 11, 12, 13, 16, 21, 22, 23, 25, 28, 29, 30, 31], "wrong": [1, 8, 15], "wrongli": 10, "wrote": [5, 11, 29], "wrt": [10, 13, 31], "wth": [10, 13, 31], "www": [20, 21, 22, 23, 27, 28, 30, 31], "wx_1": 8, "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 28, 30, 31], "x0": 8, "x1": [4, 8, 9, 10, 13], "x1_exampl": 8, "x1d": 8, "x2": [8, 9, 10, 13], "x2d": [8, 11], "x2d_train": 11, "x2dsl": 11, "x3": 8, "x_": [0, 2, 3, 5, 6, 8, 10, 11, 13, 14, 22, 25, 28, 29, 30, 31], "x_0": [0, 5, 11, 18, 22, 28, 29], "x_1": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 18, 22, 25, 28, 29, 30, 31], "x_2": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 22, 25, 28, 29, 30], "x_3": [8, 22, 25], "x_4": 22, "x_6": 18, "x_center": 11, "x_data": 1, "x_data_ful": 1, "x_hidden": 2, "x_i": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 22, 25, 28, 29, 30, 31], "x_input": 2, "x_ix_": [0, 28], "x_iy_i": 8, "x_j": [0, 2, 8, 9, 12, 16, 25, 29, 31], "x_jy_j": 8, "x_k": [12, 14, 22, 25, 29], "x_l": 25, "x_m": [6, 12, 22, 25], "x_mean": [18, 31], "x_n": [0, 2, 3, 6, 8, 11, 12, 13, 22, 25, 28, 30], "x_new": [9, 10], "x_norm": [18, 31], "x_offset": [6, 29, 31], "x_output": 2, "x_p": [3, 7, 9], "x_poli": 9, "x_poly10": 9, "x_pred": 4, "x_prev": 2, "x_reduc": 11, "x_sampl": 19, "x_scale": 8, "x_small": 13, "x_std": [18, 31], "x_t": 31, "x_test": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 29, 30, 31], "x_test_": 17, "x_test_own": 6, "x_test_scal": [0, 6, 7, 9, 10, 11, 29, 31], "x_tot": 4, "x_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "x_train_": 17, "x_train_mean": [6, 29, 31], "x_train_own": 6, "x_train_scal": [0, 6, 7, 9, 10, 11, 29, 31], "x_val": 1, "xarrai": [21, 28], "xavier": 1, "xbnew": [13, 30, 31], "xcode": [0, 21, 23, 28], "xdclassiffierconfus": 10, "xdclassiffierroc": 10, "xg_clf": 10, "xgb": 10, "xgbclassifi": 10, "xgboost": 9, "xgboot": 10, "xgbregressor": 10, "xgparam": 10, "xgtree": 10, "xi": [8, 13, 31], "xi_": 8, "xi_1": 8, "xi_i": 8, "xk": 8, "xla": [13, 21, 28], "xlabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 25, 28, 29, 30, 31], "xlim": [6, 10], "xm": 9, "xmesh": 13, "xnew": [0, 13, 28, 30, 31], "xp": 25, "xpanda": [0, 29], "xpd": [5, 11, 29], "xplot": 0, "xscale": [0, 29], "xsr": 9, "xt_x": [13, 30, 31], "xtest": 6, "xtick": [3, 6, 8, 9], "xtrain": 6, "xu": [0, 28], "xx": [0, 22, 28], "xy": [0, 6, 8, 22, 28], "xytext": 8, "xyz": [], "xz": [22, 28], "y": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "y1": 4, "y2": 4, "y3": 4, "y_": [0, 1, 5, 6, 10, 11, 22, 28, 29], "y_0": [0, 5, 11, 22, 28, 29], "y_1": [0, 5, 8, 9, 11, 13, 22, 28, 29, 30, 31], "y_1y_1": 8, "y_1y_1k": 8, "y_1y_2": 8, "y_1y_2k": 8, "y_1y_n": 8, "y_1y_nk": 8, "y_2": [0, 5, 8, 9, 11, 22, 28, 29], "y_2y_1": 8, "y_2y_1k": 8, "y_2y_2": 8, "y_2y_2k": 8, "y_3": [0, 9, 22], "y_4": 22, "y_center": [18, 31], "y_data": [0, 1, 5, 6, 28, 29, 30, 31], "y_data_ful": 1, "y_decis": 8, "y_fit": [0, 29], "y_i": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19, 22, 23, 28, 29, 30, 31], "y_if_": 10, "y_ix_": [0, 28], "y_ix_i": [7, 8, 13, 29, 30, 31], "y_iy_jk": 8, "y_j": [6, 8, 12, 23], "y_k": 12, "y_m": 22, "y_mean": [18, 31], "y_model": [0, 4, 5, 6, 28, 29, 30, 31], "y_n": [8, 13, 30, 31], "y_ny_1": 8, "y_ny_1k": 8, "y_ny_2": 8, "y_ny_2k": 8, "y_ny_n": 8, "y_ny_nk": 8, "y_offset": [6, 17, 29, 31], "y_plot": 9, "y_pred": [0, 1, 4, 6, 7, 8, 9, 10, 29, 31], "y_pred1": 9, "y_pred2": 9, "y_pred_rf": 10, "y_pred_tre": 10, "y_proba": [7, 10], "y_sampl": 19, "y_scaler": [6, 29, 31], "y_test": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 29, 30, 31], "y_test_onehot": 1, "y_test_predict": [], "y_tot": 4, "y_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 28, 29, 30, 31], "y_train_mean": [6, 29, 31], "y_train_onehot": 1, "y_train_predict": [], "y_train_scal": [6, 29, 31], "y_val": 1, "ye": [3, 6, 7], "year": [0, 21, 28], "yet": [0, 1, 6, 8, 11, 13, 20, 28], "yi": [13, 31], "yield": [0, 2, 5, 6, 8, 10, 12, 13, 14, 22, 25, 28, 30, 31], "yk": 8, "ylabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 25, 28, 29, 30, 31], "ylim": [3, 6], "ym": 9, "ymesh": 13, "yn": 0, "yo": [8, 9, 10], "yoshiki": [], "yoshua": [1, 27], "you": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31], "young": 0, "your": [1, 2, 4, 5, 6, 8, 11, 13, 15, 17, 19, 20, 21, 22, 28, 30, 31], "your_model_object": 16, "yourself": [11, 13, 28, 30], "youtu": [29, 30], "youtub": [21, 30, 31], "ypred": 6, "ypredict": [0, 13, 28, 29, 30, 31], "ypredict2": [13, 30, 31], "ypredictlasso": [5, 30], "ypredictol": [0, 5, 30], "ypredictown": [6, 29, 31], "ypredictownridg": [6, 29, 30, 31], "ypredictridg": [0, 5, 6, 29, 30, 31], "ypredictskl": [6, 29, 31], "ytest": 6, "ytick": [3, 6, 8, 9], "ytild": [0, 6, 28, 29], "ytildelasso": [5, 30], "ytildenp": [0, 28, 29], "ytildeol": [0, 5, 30], "ytildeownridg": [6, 29, 30, 31], "ytilderidg": [5, 6, 29, 30, 31], "ytrain": 6, "yuxi": 28, "yx": [22, 28], "yy": [22, 28], "yz": [22, 28], "z": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 22, 25, 28, 29], "z_": [1, 2, 12, 22, 28], "z_0": [22, 28], "z_1": [22, 28], "z_2": [22, 28], "z_c": 1, "z_h": 1, "z_hidden": 2, "z_i": [1, 12], "z_j": [1, 12], "z_k": [12, 29], "z_m": 1, "z_mod": 9, "z_o": 1, "z_output": 2, "za": [], "zaman": 25, "zaxi": 6, "zero": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 22, 23, 25, 28, 29, 30, 31], "zeros_lik": 4, "zeroth": 29, "zfill": 4, "zip": [4, 6], "zm_h": [0, 28], "zn": [], "zone": [], "zoom": 28, "zscout": [], "zx": [22, 28], "zy": [22, 28], "zz": [22, 28], "\u00f8yvind": [6, 29, 31]}, "titles": ["3. Linear Regression", "14. Building a Feed Forward Neural Network", "15. Solving Differential Equations with Deep Learning", "16. Convolutional Neural Networks", "17. Recurrent neural networks: Overarching view", "4. Ridge and Lasso Regression", "5. Resampling Methods", "6. Logistic Regression", "8. Support Vector Machines, overarching aims", "9. Decision trees, overarching aims", "10. Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods", "11. Basic ideas of the Principal Component Analysis (PCA)", "13. Neural networks", "7. Optimization, the central part of any Machine Learning algortithm", "12. Clustering and Unsupervised Learning", "Exercises week 34", "Exercises week 35", "Exercises week 36", "Exercises week 37", "Exercises week 38", "Exercises week 39", "Applied Data Analysis and Machine Learning", "2. Linear Algebra, Handling of Arrays and more Python Features", "Project 1 on Machine Learning, deadline October 6 (midnight), 2025", "Course setting", "1. Elements of Probability Theory and Statistical Data Analysis", "Teachers and Grading", "Textbooks", "Week 34: Introduction to the course, Logistics and Practicalities", "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression", "Week 36: Linear Regression and Gradient descent", "Week 37: Gradient descent methods"], "titleterms": {"": [8, 10, 30, 31], "0": [], "04": [], "05": [], "06": [], "07": [], "1": [0, 15, 16, 17, 18, 19, 20, 23, 29], "11": [], "15": 19, "19": 19, "1a": 18, "2": [0, 15, 16, 17, 18, 19, 20, 28, 29, 30], "20": [], "2017": [], "2018": [], "2019": [], "2023": 26, "2025": 23, "27": [], "2a": [], "2b": [], "3": [0, 15, 16, 17, 18, 19, 20, 29], "34": [15, 28], "35": [16, 29], "36": [17, 30], "37": [18, 31], "38": 19, "39": 20, "3a": 18, "3b": 18, "4": [0, 15, 16, 17, 18, 19, 20, 29], "4a": 18, "4b": 18, "5": [0, 16, 18, 19, 20], "6": 23, "8": 31, "A": [0, 1, 4, 8, 9, 28], "And": [28, 29, 31], "But": 31, "In": 26, "Ising": 6, "The": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 15, 21, 28, 29, 30, 31], "To": 28, "With": [4, 30], "a11i": [], "about": [28, 29, 30], "abov": 30, "abstract": 20, "accuraci": 31, "across": 31, "activ": [1, 12], "ad": [0, 6, 20, 23, 28, 29], "adaboost": 10, "adagrad": [13, 31], "adam": [13, 31], "adapt": [10, 31], "add": [], "adjust": 1, "advanc": 23, "adversari": 4, "again": [3, 9], "ai": [23, 28], "aim": [8, 9, 28], "aka": 28, "al": 31, "algebra": [22, 28], "algorithm": [9, 10, 11, 12, 28, 29, 30, 31], "algortithm": [13, 30], "all": 8, "an": [0, 4, 10, 15, 20, 28], "analys": [5, 29, 30], "analysi": [0, 5, 6, 11, 21, 23, 25, 28, 29, 30], "analyt": [0, 16, 18], "ani": [13, 30], "anoth": [9, 30], "api": [], "appli": 21, "approach": [0, 8, 14, 28, 31], "approxim": 12, "architectur": 1, "arrai": [22, 28], "assist": 26, "august": [], "author": [], "autocorrel": 25, "autograd": [2, 13, 31], "automat": [13, 31], "avali": 20, "averag": 31, "b": 23, "back": [1, 11, 12, 29, 30], "background": [21, 23], "bag": 10, "base": [13, 31], "basic": [0, 5, 7, 9, 10, 11, 22, 29, 30], "batch": [1, 31], "bay": 5, "befor": 11, "better": 8, "bia": [6, 19, 23, 31], "binari": 1, "bind": 28, "bird": 10, "blind": [], "block": [], "boldsymbol": [18, 29], "book": 19, "boost": 10, "bootstrap": [6, 10], "boston": [], "breast": 1, "brief": 28, "bring": 12, "browser": [], "build": [1, 3, 9], "c": [23, 28], "calcul": [18, 29, 30], "can": [28, 31], "cancer": [1, 7, 9, 11], "cart": 9, "case": [8, 10, 25, 29, 30, 31], "cdn": [], "cell": [], "central": [13, 21, 25, 30], "chain": 12, "challeng": 31, "chang": 10, "changelog": [], "channel": 28, "chi": [0, 28], "choic": 17, "choos": [1, 31], "cifar01": 3, "citat": [], "classic": 11, "classif": [1, 9, 10], "classifi": 8, "clip": 1, "cluster": 14, "cnn": 3, "code": [1, 2, 5, 9, 11, 12, 13, 14, 15, 16, 20, 23, 28, 29, 30, 31], "collect": [1, 3], "color": [], "colorblind": [], "combin": 31, "commun": 28, "compar": [2, 10, 16], "comparison": [30, 31], "compet": 31, "compil": [], "complet": 29, "complex": [0, 6, 23, 29], "complic": 6, "compon": 11, "comput": [9, 19, 31], "computerlab": 28, "con": [9, 31], "concept": 25, "condit": 30, "conjug": 13, "constraint": 31, "contain": [], "content": [], "contn": 28, "contrast": [], "contributor": [], "converg": 31, "convex": [8, 13, 30, 31], "convolut": [3, 12], "copyright": [], "correct": 31, "correl": [11, 29], "correspond": [], "cost": [1, 10, 29, 30, 31], "cours": [21, 24, 27, 28], "covari": [5, 11, 25, 29], "cover": 28, "creat": [16, 20], "creator": [], "cross": [6, 23], "cython": 28, "d": 23, "dark": [], "data": [0, 1, 3, 6, 7, 9, 11, 15, 17, 18, 21, 25, 28, 29], "dataset": [1, 3, 18], "david": 28, "deadlin": [23, 28], "deadllin": 26, "decai": [2, 31], "decis": [9, 10], "decomposit": [5, 11, 22, 29, 30], "deeep": [], "deep": [1, 2, 28, 31], "defin": [1, 28], "definit": 19, "deflist": [], "degre": [0, 17, 29], "deliver": [15, 16, 19, 20], "deliveri": 23, "dens": 0, "depend": [], "deriv": [5, 12, 16, 17, 19, 29, 30, 31], "descent": [2, 10, 13, 18, 23, 30, 31], "design": 29, "detail": [3, 28], "develop": 1, "diagon": 11, "differ": [8, 31], "differenti": [2, 13, 31], "diffus": 2, "dimens": 31, "dimension": [2, 3, 8, 18], "direct": [], "disadvantag": 9, "discret": 25, "discrimin": 28, "distribut": [5, 25], "do": [1, 31], "document": 20, "doe": [29, 30], "domain": 25, "down": 1, "dropout": 1, "e": 23, "economi": [29, 30], "electron": 23, "element": [0, 25, 28], "elimin": 22, "empir": 31, "energi": 28, "ensembl": 10, "entropi": 9, "environ": [0, 15], "equat": [0, 2, 12, 29, 30], "error": [0, 10, 28, 29, 30], "essenti": 28, "et": 31, "etc": 28, "euler": 2, "evalu": 1, "evid": 31, "exampl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 28, 29, 30, 31], "exercis": [0, 6, 15, 16, 17, 18, 19, 20, 29], "expect": [19, 25], "experi": 25, "explor": 0, "exponenti": [2, 31], "express": [16, 17, 19, 29], "extend": 30, "extrapol": 4, "extrem": [10, 28], "ey": 10, "f": 23, "fall": 26, "famili": [1, 28], "famou": 22, "fantast": [29, 30], "faq": [], "featur": [9, 16, 22, 29], "februari": [], "feed": [1, 12], "figur": 20, "file": [], "final": [12, 29, 31], "find": [16, 18], "fine": 1, "first": [4, 12, 28, 30], "fit": [0, 10, 15, 16, 28, 30], "fix": [29, 30, 31], "forc": 3, "forest": 10, "form": 18, "format": [23, 28], "formula": 18, "forward": [1, 2, 12], "foster": 28, "fourier": 3, "frank": 6, "freedom": [0, 17, 29], "frequent": [29, 31], "frequentist": [0, 28], "from": [5, 10, 12, 28, 29, 30, 31], "full": [2, 31], "function": [0, 1, 6, 7, 8, 10, 11, 12, 13, 23, 25, 28, 29, 30, 31], "further": [3, 5, 29, 30], "g": 23, "gan": 4, "gaussian": 22, "gd": [13, 31], "gener": [4, 9, 28], "geometr": [11, 30], "get": 20, "gini": 9, "github": 15, "goal": [15, 16, 17, 18, 19, 20], "good": [0, 20, 28], "goodfellow": 31, "gotthard": [], "grade": [26, 28], "gradient": [1, 2, 10, 13, 18, 23, 30, 31], "greativ": [], "growth": 2, "h": 23, "ha": 21, "handl": [22, 28], "hessian": [29, 30, 31], "hidden": 2, "high": [], "hous": [], "how": 16, "hyperparamet": [1, 17], "hyperplan": 8, "i": [0, 1, 28], "id3": 9, "idea": 11, "ideal": 30, "ii": 28, "illustr": 30, "implement": [1, 16, 17, 18], "implic": [5, 29, 30], "import": [5, 22, 28, 29, 30], "improv": [1, 31], "includ": [13, 23, 31], "incorpor": [], "increment": 11, "index": 9, "inform": 26, "input": 2, "instal": [21, 23, 28], "instructor": 26, "interpret": [5, 11, 19, 28, 29, 30], "introduc": [11, 13, 29], "introduct": [0, 6, 20, 21, 22, 23, 28], "invers": [5, 22], "invert": [29, 30], "ipython": [], "iter": 10, "its": 29, "j": [], "jacobian": 29, "januari": [], "jax": 13, "julia": 28, "jungl": 10, "jupyt": [], "kera": [1, 3], "kernel": [8, 11], "lab": [30, 31], "lagrangian": 8, "lasso": [5, 6, 23, 29, 30], "last": [29, 31], "later": [5, 29, 30], "layer": [1, 2, 3, 12], "learn": [0, 1, 2, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 23, 28, 29, 30, 31], "least": [5, 6, 16, 19, 23, 28, 29, 30, 31], "lectur": [28, 30, 31], "level": 10, "librari": [21, 28], "licens": [], "light": [], "likelihood": 7, "limit": [1, 13, 25, 30, 31], "linear": [0, 8, 13, 15, 22, 28, 29, 30], "link": [5, 11, 27, 29], "literatur": 23, "logist": [7, 28], "loss": [29, 30, 31], "lu": 22, "machin": [0, 8, 13, 21, 23, 28, 30], "main": [25, 28], "make": [0, 9, 10, 20, 29], "mani": [10, 12], "markdown": [], "mass": 28, "materi": [23, 28, 29, 30, 31], "math": [5, 29, 30], "mathemat": [3, 5, 8, 29, 30], "matric": [5, 22, 28], "matrix": [1, 5, 11, 12, 16, 22, 28, 29, 30, 31], "matter": 0, "max": 29, "me": [], "mean": [0, 29, 30], "meet": [5, 10, 25, 28, 29], "memori": 31, "mercer": 8, "metadata": [], "method": [6, 9, 10, 13, 23, 28, 30, 31], "metric": 19, "midnight": 23, "min": 29, "mini": 31, "minibatch": 31, "minim": 28, "mit": [], "ml": 28, "mlp": 12, "mnist": [3, 4], "model": [0, 1, 4, 6, 12, 15, 17, 28], "moment": 31, "momentum": [13, 23, 31], "mondai": [30, 31], "moon": [8, 9], "more": [3, 6, 22, 23, 28, 29, 30, 31], "motiv": 31, "move": 31, "multilay": 12, "multipl": [1, 3, 17], "multipli": 8, "myst": [], "need": [23, 28], "network": [1, 2, 3, 4, 7, 12, 28, 31], "neural": [1, 2, 3, 4, 7, 12, 28, 31], "new": [4, 18], "newton": [30, 31], "node": [], "non": [8, 31], "none": 31, "normal": [0, 1], "notat": 12, "note": [23, 29, 30], "notebook": [], "novemb": [], "now": [1, 9, 13, 30, 31], "nuclear": [0, 28], "numba": 28, "number": [0, 2, 25, 29, 31], "numer": [2, 23, 25], "numpi": [22, 28], "object": 3, "obtain": 11, "octob": 23, "od": 2, "off": [6, 19, 23], "ol": [5, 6, 15, 16, 18, 23, 30], "one": [2, 12, 18, 30], "oper": 22, "optim": [1, 8, 13, 18, 21, 28, 29, 30, 31], "order": [13, 18, 31], "ordinari": [5, 6, 16, 19, 23, 28, 29, 30, 31], "organ": [0, 28], "oslo": 27, "other": [4, 9, 11, 12, 22, 23, 28], "our": [0, 4, 5, 11, 13, 23, 28, 29, 30], "outcom": [21, 28], "output": 2, "overarch": [0, 4, 8, 9, 28, 29], "overview": [10, 28, 31], "own": [0, 10, 11, 23, 28, 29], "packag": [22, 28], "panda": [28, 29], "paramet": [28, 29], "paramt": 18, "part": [13, 21, 23, 30], "partial": 2, "pass": 1, "pca": 11, "pdf": 25, "perceptron": 12, "perform": [1, 9], "period": 3, "perspect": 1, "pitaya": [], "plan": [29, 30, 31], "plethora": 28, "point": 4, "poisson": 2, "polici": [], "polynomi": [3, 16, 18, 30], "popul": 2, "popular": 28, "practic": [13, 26, 28, 31], "pre": [1, 3], "preambl": 23, "predict": 4, "preprocess": [29, 31], "prerequisit": [3, 21, 28], "present": 20, "princip": 11, "principl": 3, "pro": [9, 31], "probabl": [5, 25], "problem": [1, 2, 13, 28, 29, 30, 31], "procedur": [9, 28], "process": [1, 3], "program": [2, 13, 23, 30, 31], "project": [6, 20, 23, 26, 28], "prop": 13, "propag": [1, 12], "properti": [5, 25, 29, 30, 31], "python": [0, 9, 15, 21, 22, 28], "quick": 8, "quickli": [], "r": 28, "random": [10, 11, 25], "raphson": 30, "rate": [23, 31], "read": [9, 28, 29, 31], "real": [6, 28], "recommend": [28, 29], "recurr": [4, 12], "reduc": [0, 29], "reduct": 3, "refer": 23, "referenc": 20, "reformul": 2, "regress": [0, 5, 6, 7, 9, 10, 13, 15, 17, 18, 19, 23, 28, 29, 30, 31], "regular": 1, "relat": [], "relev": [27, 29], "relu": 1, "remark": 3, "remind": [6, 8, 28, 29, 30, 31], "replac": [13, 31], "report": [20, 23], "repositori": 15, "requir": [2, 21], "resampl": [6, 19, 23], "rescal": [6, 29], "residu": [29, 30], "resourc": 2, "result": [29, 30], "revisit": [13, 30, 31], "rewrit": [28, 29], "ridg": [0, 5, 6, 17, 18, 19, 23, 29, 30, 31], "rm": 13, "rmsprop": 31, "role": [], "rule": [12, 31], "rung": 23, "same": [13, 31], "sampl": 11, "scalabl": 31, "scale": [17, 18, 19, 29, 31], "schedul": 28, "schemat": 9, "scheme": 2, "scienc": 28, "scikit": [0, 1, 11, 28, 29, 30, 31], "second": [13, 18, 31], "semest": 26, "sensit": 30, "septemb": [19, 30, 31], "session": [30, 31], "set": [0, 2, 3, 9, 12, 15, 24, 28, 29, 30], "setup": 15, "sgd": [13, 31], "should": 1, "show": [], "similar": [13, 31], "simpl": [0, 4, 9, 13, 18, 28, 29, 30, 31], "simplest": 18, "singl": 10, "singular": [5, 11, 29, 30], "size": [29, 30, 31], "sklearn": 16, "slightli": 31, "smoothi": [], "sneak": 31, "soft": 8, "softmax": 1, "softwar": [23, 28], "solv": [2, 30], "solver": 13, "some": [13, 22, 29, 30], "sourc": [], "specifi": 2, "speed": 31, "sphinx": [], "split": [0, 15, 29], "squar": [0, 5, 6, 10, 16, 19, 23, 28, 29, 30, 31], "standard": [13, 29], "start": 20, "state": 0, "statist": [5, 6, 21, 25, 28], "steepest": [10, 13, 30], "step": 31, "stochast": [13, 23, 25, 31], "stop": 31, "strongli": [28, 31], "structur": [], "suggest": 28, "summari": [26, 28], "superposit": 3, "supervis": 1, "support": 8, "svd": [5, 29, 30], "synthet": 18, "systemat": 3, "t": 29, "take": 16, "taken": [28, 31], "teach": 26, "teacher": [26, 28], "team": [], "technic": 29, "techniqu": [6, 11, 23], "technologi": 21, "tensorflow": [1, 3], "tent": [26, 28], "term": [], "test": [0, 1, 15, 17, 29], "texmath": [], "text": 28, "textbook": [27, 28], "than": 30, "theorem": [5, 8, 11, 12, 25], "theoret": 31, "theori": 25, "theta": 18, "thi": 28, "time": 31, "tip": [13, 31], "todo": [], "togeth": 12, "tool": [23, 28], "top": 1, "topic": 28, "toward": 11, "trade": [6, 19, 23], "tradeoff": 6, "train": [0, 1, 4, 15, 28, 29], "transform": 3, "translat": [], "tree": [9, 10], "tuesdai": 30, "tune": 1, "two": [3, 8, 21], "type": [2, 4, 12, 28], "uio": 28, "univers": [12, 27], "unsupervis": 14, "up": [0, 2, 9, 12, 15, 28, 29, 30], "updat": [23, 31], "us": [0, 1, 2, 3, 7, 13, 16, 18, 19, 21, 23, 28, 29, 30, 31], "usag": 31, "v": [3, 31], "valid": [6, 23], "valu": [5, 11, 19, 25, 29, 30], "vari": 31, "variabl": [25, 30], "varianc": [6, 19, 23], "variou": 0, "vector": [8, 12, 16, 22, 28, 29], "versu": 28, "video": 31, "view": [0, 4, 10, 29], "virtual": 15, "visual": [1, 9], "wai": [9, 23], "wave": 2, "we": [28, 31], "wednesdai": 30, "week": [15, 16, 17, 18, 19, 20, 28, 29, 30, 31], "weekli": [], "welcom": [], "what": [0, 28, 29, 30], "when": 31, "which": [1, 31], "why": [28, 31], "wisconsin": 7, "workflow": [], "write": [4, 11, 20, 23, 30], "x": 29, "xgboost": 10, "yaml": [], "yet": 30, "your": [0, 10, 16, 18, 23, 29]}}) \ No newline at end of file diff --git a/doc/LectureNotes/_build/html/statistics.html b/doc/LectureNotes/_build/html/statistics.html index 4bc6c26b2..289234ab0 100644 --- a/doc/LectureNotes/_build/html/statistics.html +++ b/doc/LectureNotes/_build/html/statistics.html @@ -232,7 +232,7 @@
    • Exercises week 37
    • Week 37: Gradient descent methods
    • Exercises week 38
      • -
    • Weekly Exercises 6
      • +
    • Exercises week 39

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

    Projects

      diff --git a/doc/LectureNotes/_build/jupyter_execute/exercisesweek39.ipynb b/doc/LectureNotes/_build/jupyter_execute/exercisesweek39.ipynb index 2c928c85c..449990270 100644 --- a/doc/LectureNotes/_build/jupyter_execute/exercisesweek39.ipynb +++ b/doc/LectureNotes/_build/jupyter_execute/exercisesweek39.ipynb @@ -5,7 +5,7 @@ "id": "433db993", "metadata": {}, "source": [ - "# Weekly Exercises 6\n", + "# Exercises week 39\n", "\n", "## Getting started with project 1\n" ] @@ -64,9 +64,21 @@ "\n", "**d)** Read the general guideline for writing a report, which can be found at .\n", "\n", - "**e)** Look at the provided example of an earlier project, found at \n" + "**e)** Look at the provided example of an earlier project, found at \n" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "338b2ee1", + "metadata": { + "vscode": { + "languageId": "plaintext" + } + }, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "id": "ec36f4c3", @@ -136,7 +148,7 @@ "\n", "**d)** Add python files for functions, and a notebook to produce the figures in exercise 2, to the Code folder. Remember to use a seed for generating random data and for train-test splits.\n", "\n", - "**e)** Create a README file in the reposotory or project folder with\n", + "**e)** Create a README file in the repository or project folder with\n", "\n", "- the name of the group members\n", "- a short description of the project\n", @@ -162,8 +174,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.15" } }, "nbformat": 4,