Morten Hjorth-Jensen
1 line
268 KiB
JavaScript
1 line
268 KiB
JavaScript
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"], [31, "a-frequentist-approach-to-data-analysis"]], "A better approach": [[8, "a-better-approach"]], "A first summary": [[31, "a-first-summary"]], "A more compact expression": [[36, "a-more-compact-expression"], [37, "a-more-compact-expression"]], "A new Cost Function": [[35, "a-new-cost-function"]], "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"], [39, "a-top-down-perspective-on-neural-networks"]], "A way to Read the Bias-Variance Tradeoff": [[35, "a-way-to-read-the-bias-variance-tradeoff"], [36, "a-way-to-read-the-bias-variance-tradeoff"]], "ADAM algorithm, taken from Goodfellow et al": [[34, "adam-algorithm-taken-from-goodfellow-et-al"]], "ADAM optimizer": [[13, "adam-optimizer"], [34, "id2"]], "Accuracy": [[34, "accuracy"]], "Activation functions": [[12, "activation-functions"], [37, "activation-functions"], [39, "activation-functions"], [39, "id3"]], "Activation functions, Logistic and Hyperbolic ones": [[37, "activation-functions-logistic-and-hyperbolic-ones"], [39, "activation-functions-logistic-and-hyperbolic-ones"]], "AdaGrad Properties": [[34, "adagrad-properties"]], "AdaGrad Update Rule Derivation": [[34, "adagrad-update-rule-derivation"]], "AdaGrad algorithm, taken from Goodfellow et al": [[34, "adagrad-algorithm-taken-from-goodfellow-et-al"]], "Adam Optimizer": [[34, "adam-optimizer"]], "Adam vs. AdaGrad and RMSProp": [[34, "adam-vs-adagrad-and-rmsprop"]], "Adam: Bias Correction": [[34, "adam-bias-correction"]], "Adam: Exponential Moving Averages (Moments)": [[34, "adam-exponential-moving-averages-moments"]], "Adam: Update Rule Derivation": [[34, "adam-update-rule-derivation"]], "Adaptive boosting: AdaBoost, Basic Algorithm": [[10, "adaptive-boosting-adaboost-basic-algorithm"]], "Adaptivity Across Dimensions": [[34, "adaptivity-across-dimensions"]], "Adding Neural Networks": [[37, "adding-neural-networks"]], "Adding a hidden layer": [[38, "adding-a-hidden-layer"], [39, "adding-a-hidden-layer"]], "Adding error analysis and training set up": [[31, "adding-error-analysis-and-training-set-up"], [32, "adding-error-analysis-and-training-set-up"]], "Adjust hyperparameters": [[1, "adjust-hyperparameters"], [39, "adjust-hyperparameters"]], "Algorithms and codes for Adagrad, RMSprop and Adam": [[34, "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": [[31, "an-optimization-minimization-problem"]], "Analyzing the last results": [[38, "analyzing-the-last-results"], [39, "analyzing-the-last-results"]], "And finally \\boldsymbol{X}\\boldsymbol{X}^T": [[32, "and-finally-boldsymbol-x-boldsymbol-x-t"]], "And finally ADAM": [[34, "and-finally-adam"]], "And what about using neural networks?": [[31, "and-what-about-using-neural-networks"]], "Another Example from Scikit-Learn\u2019s Repository": [[35, "another-example-from-scikit-learn-s-repository"], [36, "another-example-from-scikit-learn-s-repository"]], "Another Example, now with a polynomial fit": [[33, "another-example-now-with-a-polynomial-fit"]], "Another example, the moons again": [[9, "another-example-the-moons-again"]], "Applied Data Analysis and Machine Learning": [[23, null]], "Artificial neurons": [[37, "artificial-neurons"], [38, "artificial-neurons"]], "Assumptions made": [[35, "assumptions-made"]], "Autocorrelation function": [[28, "autocorrelation-function"]], "Automatic differentiation": [[13, "automatic-differentiation"], [38, "automatic-differentiation"]], "Automatic differentiation through examples": [[38, "automatic-differentiation-through-examples"]], "Back to Ridge and LASSO Regression": [[32, "back-to-ridge-and-lasso-regression"], [33, "back-to-ridge-and-lasso-regression"]], "Back to the Cancer Data": [[11, "back-to-the-cancer-data"]], "Background literature": [[25, "background-literature"], [26, "background-literature"]], "Bagging": [[10, "bagging"]], "Bagging Examples": [[10, "bagging-examples"]], "Basic Matrix Features": [[24, "basic-matrix-features"]], "Basic ideas of the Principal Component Analysis (PCA)": [[11, null]], "Basic math of the SVD": [[5, "basic-math-of-the-svd"], [32, "basic-math-of-the-svd"], [33, "basic-math-of-the-svd"]], "Basics": [[7, "basics"], [36, "basics"], [37, "basics"]], "Basics of a tree": [[9, "basics-of-a-tree"]], "Basics of an NN": [[38, "basics-of-an-nn"]], "Batch Normalization": [[1, "batch-normalization"], [39, "batch-normalization"]], "Batches and mini-batches": [[34, "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": [[38, "bringing-it-together"], [39, "bringing-it-together"]], "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 neural network code": [[39, "building-a-neural-network-code"]], "Building a tree, regression": [[9, "building-a-tree-regression"]], "Building neural networks in Tensorflow and Keras": [[1, "building-neural-networks-in-tensorflow-and-keras"], [39, "building-neural-networks-in-tensorflow-and-keras"]], "But none of these can compete with Newton\u2019s method": [[34, "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"]], "Chain rule": [[38, "chain-rule"]], "Chain rule, forward and reverse modes": [[38, "chain-rule-forward-and-reverse-modes"]], "Challenge: Choosing a Fixed Learning Rate": [[34, "challenge-choosing-a-fixed-learning-rate"]], "Choose cost function and optimizer": [[1, "choose-cost-function-and-optimizer"], [39, "choose-cost-function-and-optimizer"]], "Class of functions we can approximate": [[38, "class-of-functions-we-can-approximate"]], "Classical PCA Theorem": [[11, "classical-pca-theorem"]], "Classification and Regression, writing our own neural network code": [[26, "classification-and-regression-writing-our-own-neural-network-code"]], "Classification problems": [[36, "classification-problems"], [37, "classification-problems"]], "Clustering and Unsupervised Learning": [[14, null]], "Code Example for Cross-validation and k-fold Cross-validation": [[35, "code-example-for-cross-validation-and-k-fold-cross-validation"], [36, "code-example-for-cross-validation-and-k-fold-cross-validation"]], "Code example": [[38, "code-example"], [39, "code-example"]], "Code example for the Bootstrap method": [[35, "code-example-for-the-bootstrap-method"]], "Code for SVD and Inversion of Matrices": [[5, "code-for-svd-and-inversion-of-matrices"]], "Code with a Number of Minibatches which varies": [[34, "code-with-a-number-of-minibatches-which-varies"]], "Codes and Approaches": [[14, "codes-and-approaches"]], "Codes for the SVD": [[5, "codes-for-the-svd"], [32, "codes-for-the-svd"], [33, "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"], [39, "collect-and-pre-process-data"], [39, "id2"]], "Communication channels": [[31, "communication-channels"]], "Compact expressions": [[38, "compact-expressions"], [39, "compact-expressions"]], "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": [[33, "comparison-with-ols"]], "Completing the list": [[38, "completing-the-list"], [39, "completing-the-list"]], "Computation of gradients": [[34, "computation-of-gradients"]], "Computing the Gini index": [[9, "computing-the-gini-index"]], "Conditions on convex functions": [[33, "conditions-on-convex-functions"]], "Confidence Intervals": [[35, "confidence-intervals"]], "Conjugate gradient method": [[13, "conjugate-gradient-method"]], "Convergence rates": [[34, "convergence-rates"]], "Convex function": [[33, "convex-function"]], "Convex functions": [[13, "convex-functions"], [33, "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"], [37, "convolutional-neural-network"], [38, "convolutional-neural-network"]], "Convolutional Neural Networks": [[3, null]], "Correlation Function and Design/Feature Matrix": [[32, "correlation-function-and-design-feature-matrix"]], "Correlation Matrix": [[11, "correlation-matrix"], [32, "correlation-matrix"]], "Correlation Matrix with Pandas": [[32, "correlation-matrix-with-pandas"]], "Cost functions": [[39, "cost-functions"]], "Counting the number of floating point operations": [[38, "counting-the-number-of-floating-point-operations"]], "Course Format": [[31, "course-format"]], "Course setting": [[27, null]], "Covariance Matrix Examples": [[32, "covariance-matrix-examples"]], "Covariance and Correlation Matrix": [[32, "covariance-and-correlation-matrix"]], "Cross-validation": [[6, "cross-validation"]], "Cross-validation in brief": [[35, "cross-validation-in-brief"], [36, "cross-validation-in-brief"]], "Deadlines for projects (tentative)": [[31, "deadlines-for-projects-tentative"]], "Decision trees, overarching aims": [[9, null]], "Deep Neural Networks": [[34, "deep-neural-networks"]], "Deep learning methods": [[31, "deep-learning-methods"]], "Define model and architecture": [[1, "define-model-and-architecture"], [39, "define-model-and-architecture"]], "Defining intermediate operations": [[38, "defining-intermediate-operations"]], "Defining the cost function": [[1, "defining-the-cost-function"], [39, "defining-the-cost-function"]], "Definitions": [[19, "definitions"], [38, "definitions"], [39, "definitions"]], "Deliverables": [[15, "deliverables"], [16, "deliverables"], [19, "deliverables"], [20, "deliverables"], [25, "deliverables"], [26, "deliverables"]], "Derivation of the AdaGrad Algorithm": [[34, "derivation-of-the-adagrad-algorithm"]], "Derivative of the cost function": [[38, "derivative-of-the-cost-function"], [39, "derivative-of-the-cost-function"]], "Derivatives and the chain rule": [[12, "derivatives-and-the-chain-rule"], [38, "derivatives-and-the-chain-rule"], [39, "derivatives-and-the-chain-rule"]], "Derivatives in terms of z_j^L": [[38, "derivatives-in-terms-of-z-j-l"], [39, "derivatives-in-terms-of-z-j-l"]], "Derivatives of the hidden layer": [[38, "derivatives-of-the-hidden-layer"], [39, "derivatives-of-the-hidden-layer"]], "Derivatives, example 1": [[32, "derivatives-example-1"]], "Deriving OLS from a probability distribution": [[5, "deriving-ols-from-a-probability-distribution"], [35, "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": [[32, "deriving-the-lasso-regression-equations"], [33, "deriving-the-lasso-regression-equations"], [33, "id6"]], "Deriving the Ridge Regression Equations": [[32, "deriving-the-ridge-regression-equations"], [33, "deriving-the-ridge-regression-equations"], [33, "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"], [39, "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": [[31, "discriminative-modeling"]], "Discussing the correlation data": [[37, "discussing-the-correlation-data"]], "Does Logistic Regression do a better Job?": [[37, "does-logistic-regression-do-a-better-job"]], "Domains and probabilities": [[28, "domains-and-probabilities"]], "Dropout": [[1, "dropout"], [39, "dropout"]], "ELU function": [[39, "elu-function"]], "Economy-size SVD": [[32, "economy-size-svd"], [33, "economy-size-svd"]], "Elements of Probability Theory and Statistical Data Analysis": [[28, null]], "Empirical Evidence: Convergence Time and Memory in Practice": [[34, "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": [[31, "essential-elements-of-ml"]], "Evaluate model performance on test data": [[1, "evaluate-model-performance-on-test-data"], [39, "evaluate-model-performance-on-test-data"]], "Example 2": [[32, "example-2"]], "Example 3": [[32, "example-3"]], "Example 4": [[32, "example-4"]], "Example Matrix": [[32, "example-matrix"], [33, "example-matrix"]], "Example code for Bias-Variance tradeoff": [[35, "example-code-for-bias-variance-tradeoff"]], "Example code for Logistic Regression": [[36, "example-code-for-logistic-regression"], [37, "example-code-for-logistic-regression"]], "Example of discriminative modeling, taken from Generative Deep Learning by David Foster": [[31, "example-of-discriminative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of generative modeling, taken from Generative Deep Learning by David Foster": [[31, "example-of-generative-modeling-taken-from-generative-deep-learning-by-david-foster"]], "Example of own Standard scaling": [[32, "example-of-own-standard-scaling"]], "Example relevant for the exercises": [[32, "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"], [39, "example-binary-classification-problem"]], "Examples": [[31, "examples"]], "Examples of XOR, OR and AND gates": [[37, "examples-of-xor-or-and-and-gates"]], "Examples of likelihood functions used in logistic regression and neural networks": [[7, "examples-of-likelihood-functions-used-in-logistic-regression-and-neural-networks"]], "Examples of likelihood functions used in logistic regression and nueral networks": [[36, "examples-of-likelihood-functions-used-in-logistic-regression-and-nueral-networks"]], "Exercise 1": [[21, "exercise-1"]], "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 - Understand the feed forward pass": [[22, "exercise-1-understand-the-feed-forward-pass"]], "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: Including more data": [[38, "exercise-1-including-more-data"]], "Exercise 1: Setting up various Python environments": [[0, "exercise-1-setting-up-various-python-environments"]], "Exercise 2": [[21, "exercise-2"]], "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 - Gradient with one layer using autograd": [[22, "exercise-2-gradient-with-one-layer-using-autograd"]], "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: Extended program": [[38, "exercise-2-extended-program"]], "Exercise 2: making your own data and exploring scikit-learn": [[0, "exercise-2-making-your-own-data-and-exploring-scikit-learn"]], "Exercise 3": [[21, "exercise-3"]], "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 - Gradient with one layer writing backpropagation by hand": [[22, "exercise-3-gradient-with-one-layer-writing-backpropagation-by-hand"]], "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 - Custom activation for each layer": [[21, "exercise-4-custom-activation-for-each-layer"]], "Exercise 4 - Fitting a polynomial": [[16, "exercise-4-fitting-a-polynomial"]], "Exercise 4 - Gradient with two layers writing backpropagation by hand": [[22, "exercise-4-gradient-with-two-layers-writing-backpropagation-by-hand"]], "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 available and presentable": [[20, "exercise-4-making-the-code-available-and-presentable"]], "Exercise 5 - Comparing your code with sklearn": [[16, "exercise-5-comparing-your-code-with-sklearn"]], "Exercise 5 - Gradient with any number of layers writing backpropagation by hand": [[22, "exercise-5-gradient-with-any-number-of-layers-writing-backpropagation-by-hand"]], "Exercise 5 - Processing multiple inputs at once": [[21, "exercise-5-processing-multiple-inputs-at-once"]], "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 6 - Batched inputs": [[22, "exercise-6-batched-inputs"]], "Exercise 6 - Predicting on real data": [[21, "exercise-6-predicting-on-real-data"]], "Exercise 7 - Training": [[22, "exercise-7-training"]], "Exercise 7 - Training on real data (Optional)": [[21, "exercise-7-training-on-real-data-optional"]], "Exercise 8 (Optional) - Object orientation": [[22, "exercise-8-optional-object-orientation"]], "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]], "Exercises week 41": [[21, null]], "Exercises week 42": [[22, null]], "Expectation value and variance": [[35, "expectation-value-and-variance"]], "Expectation value and variance for \\boldsymbol{\\theta}": [[35, "expectation-value-and-variance-for-boldsymbol-theta"]], "Expectation values": [[28, "expectation-values"]], "Explicit derivatives": [[38, "explicit-derivatives"], [39, "explicit-derivatives"]], "Exploding gradients": [[39, "exploding-gradients"]], "Extending to more predictors": [[36, "extending-to-more-predictors"], [37, "extending-to-more-predictors"]], "Extending to more than one variable": [[33, "extending-to-more-than-one-variable"]], "Extremely useful tools, strongly recommended": [[31, "extremely-useful-tools-strongly-recommended"]], "Feed-forward neural networks": [[12, "feed-forward-neural-networks"], [37, "feed-forward-neural-networks"], [38, "feed-forward-neural-networks"]], "Feed-forward pass": [[1, "feed-forward-pass"], [39, "feed-forward-pass"]], "Final back propagating equation": [[12, "final-back-propagating-equation"], [38, "final-back-propagating-equation"], [39, "final-back-propagating-equation"]], "Final derivatives": [[38, "final-derivatives"]], "Final expression": [[38, "final-expression"], [39, "final-expression"]], "Final expressions for the biases of the hidden layer": [[38, "final-expressions-for-the-biases-of-the-hidden-layer"], [39, "final-expressions-for-the-biases-of-the-hidden-layer"]], "Finding the Limit": [[35, "finding-the-limit"]], "Fine-tuning neural network hyperparameters": [[1, "fine-tuning-neural-network-hyperparameters"], [39, "fine-tuning-neural-network-hyperparameters"]], "First network example, simple percepetron with one input": [[38, "first-network-example-simple-percepetron-with-one-input"]], "Fitting an Equation of State for Dense Nuclear Matter": [[0, "fitting-an-equation-of-state-for-dense-nuclear-matter"]], "Fixing the singularity": [[32, "fixing-the-singularity"], [33, "fixing-the-singularity"]], "Format for electronic delivery of report and programs": [[25, "format-for-electronic-delivery-of-report-and-programs"], [26, "format-for-electronic-delivery-of-report-and-programs"]], "Forward and reverse modes": [[38, "forward-and-reverse-modes"]], "Frequently used scaling functions": [[32, "frequently-used-scaling-functions"], [34, "frequently-used-scaling-functions"]], "From OLS to Ridge and Lasso": [[33, "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"]], "Full object-oriented implementation": [[39, "full-object-oriented-implementation"]], "Functionality in Scikit-Learn": [[32, "functionality-in-scikit-learn"], [34, "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"], [32, "further-properties-important-for-our-analyses-later"], [33, "further-properties-important-for-our-analyses-later"]], "Gaussian Elimination": [[24, "gaussian-elimination"]], "General Features": [[9, "general-features"]], "General linear models and linear algebra": [[31, "general-linear-models-and-linear-algebra"]], "Generalizing the fitting procedure as a linear algebra problem": [[31, "generalizing-the-fitting-procedure-as-a-linear-algebra-problem"], [31, "id1"]], "Generative Adversarial Networks": [[4, "generative-adversarial-networks"]], "Generative Models": [[4, "generative-models"]], "Generative Versus Discriminative Modeling": [[31, "generative-versus-discriminative-modeling"]], "Geometric Interpretation and link with Singular Value Decomposition": [[11, "geometric-interpretation-and-link-with-singular-value-decomposition"]], "Getting serious, the back propagation equations for a neural network": [[38, "getting-serious-the-back-propagation-equations-for-a-neural-network"]], "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"], [39, "gradient-clipping"]], "Gradient Descent Example": [[33, "id1"], [34, "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": [[33, "gradient-descent-and-ridge"], [34, "gradient-descent-and-ridge"]], "Gradient descent and revisiting Ordinary Least Squares from last week": [[34, "gradient-descent-and-revisiting-ordinary-least-squares-from-last-week"]], "Gradient descent example": [[33, "gradient-descent-example"], [34, "gradient-descent-example"]], "Gradient expressions": [[38, "gradient-expressions"], [39, "gradient-expressions"]], "Grading": [[29, "grading"], [29, "id2"], [31, "grading"]], "Hidden layers": [[39, "hidden-layers"]], "Homogeneous data": [[39, "homogeneous-data"]], "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"]], "Identifying Terms": [[35, "identifying-terms"]], "Illustration of a single perceptron model and a multi-perceptron model": [[37, "illustration-of-a-single-perceptron-model-and-a-multi-perceptron-model"], [38, "illustration-of-a-single-perceptron-model-and-a-multi-perceptron-model"]], "Important Matrix and vector handling packages": [[24, "important-matrix-and-vector-handling-packages"]], "Important observations": [[38, "important-observations"], [39, "important-observations"]], "Important technicalities: More on Rescaling data": [[32, "important-technicalities-more-on-rescaling-data"]], "Improving gradient descent with momentum": [[34, "improving-gradient-descent-with-momentum"]], "Improving performance": [[1, "improving-performance"], [39, "improving-performance"]], "In general not this simple": [[38, "in-general-not-this-simple"]], "In summary": [[29, "in-summary"]], "Including Stochastic Gradient Descent with Autograd": [[13, "including-stochastic-gradient-descent-with-autograd"], [34, "including-stochastic-gradient-descent-with-autograd"]], "Including more classes": [[36, "including-more-classes"], [37, "including-more-classes"]], "Incremental PCA": [[11, "incremental-pca"]], "Independent and Identically Distributed (iid)": [[35, "independent-and-identically-distributed-iid"]], "Inputs to the activation function": [[38, "inputs-to-the-activation-function"], [39, "inputs-to-the-activation-function"]], "Insights from the paper by Glorot and Bengio": [[39, "insights-from-the-paper-by-glorot-and-bengio"]], "Installing R, C++, cython or Julia": [[31, "installing-r-c-cython-or-julia"]], "Installing R, C++, cython, Numba etc": [[31, "installing-r-c-cython-numba-etc"]], "Instructor information": [[29, "instructor-information"]], "Interpretations and optimizing our parameters": [[31, "interpretations-and-optimizing-our-parameters"], [31, "id2"], [31, "id3"], [32, "interpretations-and-optimizing-our-parameters"], [32, "id1"], [32, "id2"]], "Interpreting the Ridge results": [[32, "interpreting-the-ridge-results"], [33, "interpreting-the-ridge-results"], [33, "id4"]], "Introducing JAX": [[13, "introducing-jax"]], "Introducing the Covariance and Correlation functions": [[11, "introducing-the-covariance-and-correlation-functions"], [32, "introducing-the-covariance-and-correlation-functions"]], "Introduction": [[0, "introduction"], [6, "introduction"], [23, "introduction"], [24, "introduction"]], "Introduction to Neural networks": [[37, "introduction-to-neural-networks"], [38, "introduction-to-neural-networks"]], "Introduction to numerical projects": [[25, "introduction-to-numerical-projects"], [26, "introduction-to-numerical-projects"]], "Is the Logistic activation function (Sigmoid) our choice?": [[39, "is-the-logistic-activation-function-sigmoid-our-choice"]], "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": [[24, "lu-decomposition-the-inverse-of-a-matrix"]], "Lab sessions Tuesday and Wednesday": [[37, "lab-sessions-tuesday-and-wednesday"]], "Lab sessions on Tuesday and Wednesday": [[38, "lab-sessions-on-tuesday-and-wednesday"]], "Lab sessions week 39": [[36, "lab-sessions-week-39"]], "Lasso Regression": [[33, "lasso-regression"]], "Lasso case": [[33, "lasso-case"]], "Layers": [[1, "layers"], [39, "layers"]], "Layers used to build CNNs": [[3, "layers-used-to-build-cnns"]], "Layout of a neural network with three hidden layers": [[38, "layout-of-a-neural-network-with-three-hidden-layers"]], "Layout of a neural network with three hidden layers (last layer = l=L=4, first layer l=0)": [[39, "layout-of-a-neural-network-with-three-hidden-layers-last-layer-l-l-4-first-layer-l-0"]], "Layout of a simple neural network with no hidden layer": [[38, "layout-of-a-simple-neural-network-with-no-hidden-layer"], [39, "layout-of-a-simple-neural-network-with-no-hidden-layer"]], "Layout of a simple neural network with one hidden layer": [[38, "layout-of-a-simple-neural-network-with-one-hidden-layer"], [39, "layout-of-a-simple-neural-network-with-one-hidden-layer"]], "Layout of a simple neural network with two input nodes, one hidden layer and one output node": [[38, "layout-of-a-simple-neural-network-with-two-input-nodes-one-hidden-layer-and-one-output-node"]], "Layout of a simple neural network with two input nodes, one hidden layer with two hidden noeds and one output node": [[39, "layout-of-a-simple-neural-network-with-two-input-nodes-one-hidden-layer-with-two-hidden-noeds-and-one-output-node"]], "Layout of input to first hidden layer l=1 from input layer l=0": [[39, "layout-of-input-to-first-hidden-layer-l-1-from-input-layer-l-0"]], "Learning goals": [[15, "learning-goals"], [16, "learning-goals"], [17, "learning-goals"], [18, "learning-goals"], [19, "learning-goals"], [20, "learning-goals"]], "Learning outcomes": [[23, "learning-outcomes"], [31, "learning-outcomes"]], "Learning rate methods": [[39, "learning-rate-methods"]], "Lecture Monday October 6": [[38, "lecture-monday-october-6"]], "Lecture Monday September 29, 2025": [[37, "lecture-monday-september-29-2025"]], "Lecture October 13, 2025": [[39, "lecture-october-13-2025"]], "Lecture material": [[36, "lecture-material"]], "Lecture material: Writing a code which implements a feed-forward neural network": [[39, "lecture-material-writing-a-code-which-implements-a-feed-forward-neural-network"]], "Lectures and ComputerLab": [[31, "lectures-and-computerlab"]], "Limitations of NNs": [[39, "limitations-of-nns"]], "Limitations of supervised learning with deep networks": [[1, "limitations-of-supervised-learning-with-deep-networks"], [39, "limitations-of-supervised-learning-with-deep-networks"]], "Linear Algebra, Handling of Arrays and more Python Features": [[24, null]], "Linear Regression": [[0, null]], "Linear Regression Problems": [[32, "linear-regression-problems"], [33, "linear-regression-problems"]], "Linear Regression and the SVD": [[33, "linear-regression-and-the-svd"]], "Linear Regression, basic elements": [[0, "linear-regression-basic-elements"]], "Linear classifier": [[36, "linear-classifier"]], "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"], [35, "linking-the-regression-analysis-with-a-statistical-interpretation"]], "Linking with the SVD": [[5, "linking-with-the-svd"], [32, "linking-with-the-svd"]], "Links to relevant courses at the University of Oslo": [[30, "links-to-relevant-courses-at-the-university-of-oslo"]], "Logistic Regression": [[7, null], [7, "id1"], [36, "logistic-regression"]], "Logistic Regression, from last week": [[37, "logistic-regression-from-last-week"]], "Logistic function as the root of problems": [[39, "logistic-function-as-the-root-of-problems"]], "MNIST and GANs": [[4, "mnist-and-gans"]], "Machine Learning": [[31, "machine-learning"]], "Machine learning": [[23, "machine-learning"]], "Main textbooks": [[31, "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": [[32, "making-your-own-test-train-splitting"]], "Material for exercises week 35": [[32, "material-for-exercises-week-35"]], "Material for lab sessions sessions Tuesday and Wednesday": [[33, "material-for-lab-sessions-sessions-tuesday-and-wednesday"]], "Material for lecture Monday September 2": [[33, "material-for-lecture-monday-september-2"]], "Material for lecture Monday September 8": [[34, "material-for-lecture-monday-september-8"]], "Material for the lab sessions": [[34, "material-for-the-lab-sessions"], [35, "material-for-the-lab-sessions"]], "Material for the lab sessions on Tuesday and Wednesday": [[39, "material-for-the-lab-sessions-on-tuesday-and-wednesday"]], "Material for the lecture on Monday October 6, 2025": [[38, "material-for-the-lecture-on-monday-october-6-2025"]], "Mathematical Interpretation of Ordinary Least Squares": [[5, "mathematical-interpretation-of-ordinary-least-squares"], [32, "mathematical-interpretation-of-ordinary-least-squares"], [33, "mathematical-interpretation-of-ordinary-least-squares"]], "Mathematical model": [[37, "mathematical-model"], [37, "id1"], [37, "id2"], [37, "id3"], [37, "id4"]], "Mathematical optimization of convex functions": [[8, "mathematical-optimization-of-convex-functions"]], "Mathematics of CNNs": [[3, "mathematics-of-cnns"]], "Mathematics of deep learning": [[38, "mathematics-of-deep-learning"], [39, "mathematics-of-deep-learning"]], "Mathematics of deep learning and neural networks": [[38, "mathematics-of-deep-learning-and-neural-networks"]], "Mathematics of the SVD and implications": [[5, "mathematics-of-the-svd-and-implications"], [32, "mathematics-of-the-svd-and-implications"], [33, "mathematics-of-the-svd-and-implications"]], "Matrices in Python": [[31, "matrices-in-python"]], "Matrix multiplication": [[1, "matrix-multiplication"], [39, "matrix-multiplication"]], "Matrix multiplications": [[39, "matrix-multiplications"]], "Matrix-vector notation": [[37, "matrix-vector-notation"]], "Matrix-vector notation and activation": [[12, "matrix-vector-notation-and-activation"], [37, "matrix-vector-notation-and-activation"]], "Maximum Likelihood Estimation (MLE)": [[35, "maximum-likelihood-estimation-mle"]], "Maximum likelihood": [[36, "maximum-likelihood"], [37, "maximum-likelihood"]], "Meet the covariance!": [[28, "meet-the-covariance"]], "Meet the Covariance Matrix": [[5, "meet-the-covariance-matrix"], [32, "meet-the-covariance-matrix"]], "Meet the Hessian Matrix": [[32, "meet-the-hessian-matrix"]], "Meet the Pandas": [[31, "meet-the-pandas"]], "Memory Usage and Scalability": [[34, "memory-usage-and-scalability"]], "Memory constraints": [[34, "memory-constraints"]], "Min-Max Scaling": [[32, "min-max-scaling"]], "Minimizing the cross entropy": [[36, "minimizing-the-cross-entropy"], [37, "minimizing-the-cross-entropy"]], "Momentum based GD": [[13, "momentum-based-gd"], [34, "momentum-based-gd"]], "More classes": [[36, "more-classes"], [37, "more-classes"]], "More complicated Example: The Ising model": [[6, "more-complicated-example-the-ising-model"]], "More complicated function": [[38, "more-complicated-function"]], "More considerations": [[38, "more-considerations"], [39, "more-considerations"]], "More examples on bootstrap and cross-validation and errors": [[35, "more-examples-on-bootstrap-and-cross-validation-and-errors"], [36, "more-examples-on-bootstrap-and-cross-validation-and-errors"]], "More interpretations": [[32, "more-interpretations"], [33, "more-interpretations"], [33, "id5"]], "More limitations": [[39, "more-limitations"]], "More on Dimensionalities": [[3, "more-on-dimensionalities"]], "More on Rescaling data": [[6, "more-on-rescaling-data"]], "More on Steepest descent": [[33, "more-on-steepest-descent"]], "More on activation functions, output layers": [[39, "more-on-activation-functions-output-layers"]], "More on convex functions": [[33, "more-on-convex-functions"]], "More on the general approximation theorem": [[38, "more-on-the-general-approximation-theorem"]], "More preprocessing": [[32, "more-preprocessing"], [34, "more-preprocessing"]], "More top-down perspectives": [[39, "more-top-down-perspectives"]], "Motivation for Adaptive Step Sizes": [[34, "motivation-for-adaptive-step-sizes"]], "Multiclass classification": [[39, "multiclass-classification"]], "Multilayer perceptrons": [[12, "multilayer-perceptrons"], [37, "multilayer-perceptrons"], [38, "multilayer-perceptrons"]], "Multivariable functions": [[38, "multivariable-functions"]], "Network requirements": [[2, "network-requirements"]], "Neural Networks vs CNNs": [[3, "neural-networks-vs-cnns"]], "Neural network types": [[37, "neural-network-types"], [38, "neural-network-types"]], "Neural networks": [[12, null]], "New expression for the derivative": [[38, "new-expression-for-the-derivative"]], "Non-Convex Problems": [[34, "non-convex-problems"]], "Note about SVD Calculations": [[32, "note-about-svd-calculations"], [33, "note-about-svd-calculations"]], "Note on Scikit-Learn": [[33, "note-on-scikit-learn"]], "Numerical experiments and the covariance, central limit theorem": [[28, "numerical-experiments-and-the-covariance-central-limit-theorem"]], "Numpy and arrays": [[24, "numpy-and-arrays"], [31, "numpy-and-arrays"]], "Numpy examples and Important Matrix and vector handling packages": [[31, "numpy-examples-and-important-matrix-and-vector-handling-packages"]], "Optimization and Deep learning": [[36, "optimization-and-deep-learning"], [37, "optimization-and-deep-learning"]], "Optimization and gradient descent, the central part of any Machine Learning algortithm": [[33, "optimization-and-gradient-descent-the-central-part-of-any-machine-learning-algortithm"]], "Optimization, the central part of any Machine Learning algortithm": [[13, null], [36, "optimization-the-central-part-of-any-machine-learning-algortithm"], [37, "optimization-the-central-part-of-any-machine-learning-algortithm"]], "Optimizing our parameters": [[31, "optimizing-our-parameters"]], "Optimizing our parameters, more details": [[31, "optimizing-our-parameters-more-details"]], "Optimizing the cost function": [[1, "optimizing-the-cost-function"], [39, "optimizing-the-cost-function"]], "Optimizing the parameters": [[38, "optimizing-the-parameters"], [39, "optimizing-the-parameters"]], "Organizing our data": [[0, "organizing-our-data"], [31, "organizing-our-data"]], "Other Matrix and Vector Operations": [[24, "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": [[31, "other-courses-on-data-science-and-machine-learning-at-uio"]], "Other courses on Data science and Machine Learning at UiO, contn": [[31, "other-courses-on-data-science-and-machine-learning-at-uio-contn"]], "Other ingredients of a neural network": [[38, "other-ingredients-of-a-neural-network"]], "Other measures in classification studies": [[37, "other-measures-in-classification-studies"]], "Other parameters": [[38, "other-parameters"]], "Other popular texts": [[31, "other-popular-texts"]], "Other techniques": [[11, "other-techniques"]], "Other types of networks": [[12, "other-types-of-networks"], [37, "other-types-of-networks"], [38, "other-types-of-networks"]], "Other ways of visualizing the trees": [[9, "other-ways-of-visualizing-the-trees"]], "Our model for the nuclear binding energies": [[31, "our-model-for-the-nuclear-binding-energies"]], "Output layer": [[38, "output-layer"], [39, "output-layer"]], "Overarching aims of the exercises this week": [[21, "overarching-aims-of-the-exercises-this-week"], [22, "overarching-aims-of-the-exercises-this-week"]], "Overarching view of a neural network": [[38, "overarching-view-of-a-neural-network"]], "Overview of first week": [[31, "overview-of-first-week"]], "Overview video on Stochastic Gradient Descent (SGD)": [[34, "overview-video-on-stochastic-gradient-descent-sgd"]], "Own code for Ordinary Least Squares": [[31, "own-code-for-ordinary-least-squares"], [32, "own-code-for-ordinary-least-squares"]], "PCA and scikit-learn": [[11, "pca-and-scikit-learn"]], "Pandas AI": [[31, "pandas-ai"]], "Parameters of neural networks": [[38, "parameters-of-neural-networks"]], "Part a : Ordinary Least Square (OLS) for the Runge function": [[25, "part-a-ordinary-least-square-ols-for-the-runge-function"]], "Part a): Analytical warm-up": [[26, "part-a-analytical-warm-up"]], "Part b): Writing your own Neural Network code": [[26, "part-b-writing-your-own-neural-network-code"]], "Part b: Adding Ridge regression for the Runge function": [[25, "part-b-adding-ridge-regression-for-the-runge-function"]], "Part c): Testing against other software libraries": [[26, "part-c-testing-against-other-software-libraries"]], "Part c: Writing your own gradient descent code": [[25, "part-c-writing-your-own-gradient-descent-code"]], "Part d): Testing different activation functions and depths of the neural network": [[26, "part-d-testing-different-activation-functions-and-depths-of-the-neural-network"]], "Part d: Including momentum and more advanced ways to update the learning the rate": [[25, "part-d-including-momentum-and-more-advanced-ways-to-update-the-learning-the-rate"]], "Part e): Testing different norms": [[26, "part-e-testing-different-norms"]], "Part e: Writing our own code for Lasso regression": [[25, "part-e-writing-our-own-code-for-lasso-regression"]], "Part f): Classification analysis using neural networks": [[26, "part-f-classification-analysis-using-neural-networks"]], "Part f: Stochastic gradient descent": [[25, "part-f-stochastic-gradient-descent"]], "Part g) Critical evaluation of the various algorithms": [[26, "part-g-critical-evaluation-of-the-various-algorithms"]], "Part g: Bias-variance trade-off and resampling techniques": [[25, "part-g-bias-variance-trade-off-and-resampling-techniques"]], "Part h): Cross-validation as resampling techniques, adding more complexity": [[25, "part-h-cross-validation-as-resampling-techniques-adding-more-complexity"]], "Partial Differential Equations": [[2, "partial-differential-equations"]], "Plan for week 39, September 22-26, 2025": [[36, "plan-for-week-39-september-22-26-2025"]], "Plan for week 41, October 6-10": [[38, "plan-for-week-41-october-6-10"]], "Plans for week 35": [[32, "plans-for-week-35"]], "Plans for week 36": [[33, "plans-for-week-36"]], "Plans for week 37, lecture Monday": [[34, "plans-for-week-37-lecture-monday"]], "Plans for week 38, lecture Monday September 15": [[35, "plans-for-week-38-lecture-monday-september-15"]], "Plotting the Histogram": [[35, "plotting-the-histogram"]], "Plotting the mean value for each group": [[36, "plotting-the-mean-value-for-each-group"]], "Practical tips": [[13, "practical-tips"], [34, "practical-tips"]], "Practicalities": [[29, "practicalities"], [29, "id1"]], "Preamble: Note on writing reports, using reference material, AI and other tools": [[25, "preamble-note-on-writing-reports-using-reference-material-ai-and-other-tools"], [26, "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": [[32, "preprocessing-our-data"]], "Prerequisites": [[31, "prerequisites"]], "Prerequisites and background": [[23, "prerequisites-and-background"]], "Prerequisites: Collect and pre-process data": [[3, "prerequisites-collect-and-pre-process-data"]], "Probability Distribution Functions": [[28, "probability-distribution-functions"]], "Program example for gradient descent with Ridge Regression": [[33, "program-example-for-gradient-descent-with-ridge-regression"], [34, "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": [[25, null]], "Project 2 on Machine Learning, deadline November 10 (Midnight)": [[26, null]], "Properties of PDFs": [[28, "properties-of-pdfs"]], "Pros and cons": [[34, "pros-and-cons"]], "Pros and cons of trees, pros": [[9, "pros-and-cons-of-trees-pros"]], "Python installers": [[23, "python-installers"], [31, "python-installers"]], "RMS prop": [[13, "rms-prop"]], "RMSProp algorithm, taken from Goodfellow et al": [[34, "rmsprop-algorithm-taken-from-goodfellow-et-al"]], "RMSProp: Adaptive Learning Rates": [[34, "rmsprop-adaptive-learning-rates"]], "RMSprop for adaptive learning rate with Stochastic Gradient Descent": [[34, "rmsprop-for-adaptive-learning-rate-with-stochastic-gradient-descent"]], "Random Numbers": [[28, "random-numbers"]], "Random forests": [[10, "random-forests"]], "Randomized PCA": [[11, "randomized-pca"]], "Reading material": [[31, "reading-material"]], "Reading recommendations": [[39, "reading-recommendations"]], "Reading recommendations:": [[32, "reading-recommendations"]], "Reading suggestions week 34": [[31, "reading-suggestions-week-34"]], "Readings and Videos": [[35, "readings-and-videos"]], "Readings and Videos, logistic regression": [[36, "readings-and-videos-logistic-regression"]], "Readings and Videos, resampling methods": [[36, "readings-and-videos-resampling-methods"]], "Readings and Videos:": [[34, "readings-and-videos"], [38, "readings-and-videos"]], "Readings and videos": [[39, "readings-and-videos"]], "Recurrent neural networks": [[12, "recurrent-neural-networks"], [37, "recurrent-neural-networks"], [38, "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"], [32, "reducing-the-number-of-degrees-of-freedom-overarching-view"]], "Reducing the number of operations": [[38, "reducing-the-number-of-operations"]], "Reformulating the problem": [[2, "reformulating-the-problem"]], "Regression Case": [[10, "regression-case"]], "Regression analysis and resampling methods": [[25, "regression-analysis-and-resampling-methods"]], "Regression analysis, overarching aims": [[31, "regression-analysis-overarching-aims"]], "Regression analysis, overarching aims II": [[31, "regression-analysis-overarching-aims-ii"]], "Regularization": [[1, "regularization"], [39, "regularization"]], "Relevance": [[37, "relevance"], [39, "relevance"]], "Reminder about the gradient machinery from project 1": [[26, "reminder-about-the-gradient-machinery-from-project-1"]], "Reminder from last week": [[32, "reminder-from-last-week"]], "Reminder from last week: First network example, simple percepetron with one input": [[39, "reminder-from-last-week-first-network-example-simple-percepetron-with-one-input"]], "Reminder on Newton-Raphson\u2019s method": [[33, "reminder-on-newton-raphson-s-method"]], "Reminder on Statistics": [[6, "reminder-on-statistics"]], "Reminder on books with hands-on material and codes": [[38, "reminder-on-books-with-hands-on-material-and-codes"], [39, "reminder-on-books-with-hands-on-material-and-codes"]], "Reminder on different scaling methods": [[34, "reminder-on-different-scaling-methods"]], "Reminder on the chain rule and gradients": [[38, "reminder-on-the-chain-rule-and-gradients"]], "Replace or not": [[13, "replace-or-not"], [34, "replace-or-not"]], "Required Technologies": [[23, "required-technologies"]], "Resampling Methods": [[6, null]], "Resampling and the Bias-Variance Trade-off": [[19, "resampling-and-the-bias-variance-trade-off"]], "Resampling approaches can be computationally expensive": [[35, "resampling-approaches-can-be-computationally-expensive"], [36, "resampling-approaches-can-be-computationally-expensive"]], "Resampling methods": [[6, "id1"], [35, "resampling-methods"], [35, "id2"], [36, "resampling-methods"], [36, "id1"]], "Resampling methods: Bootstrap": [[35, "resampling-methods-bootstrap"], [36, "resampling-methods-bootstrap"]], "Resampling methods: Bootstrap approach": [[35, "resampling-methods-bootstrap-approach"]], "Resampling methods: Bootstrap background": [[35, "resampling-methods-bootstrap-background"]], "Resampling methods: Bootstrap steps": [[35, "resampling-methods-bootstrap-steps"]], "Resampling methods: More Bootstrap background": [[35, "resampling-methods-more-bootstrap-background"]], "Residual Error": [[32, "residual-error"], [33, "residual-error"]], "Resources on differential equations and deep learning": [[2, "resources-on-differential-equations-and-deep-learning"]], "Revisiting Ordinary Least Squares": [[33, "revisiting-ordinary-least-squares"]], "Revisiting our Linear Regression Solvers": [[13, "revisiting-our-linear-regression-solvers"]], "Revisiting our Logistic Regression case": [[36, "revisiting-our-logistic-regression-case"], [37, "revisiting-our-logistic-regression-case"]], "Rewriting the Covariance and/or Correlation Matrix": [[32, "rewriting-the-covariance-and-or-correlation-matrix"]], "Rewriting the \\delta-function": [[35, "rewriting-the-delta-function"]], "Rewriting the fitting procedure as a linear algebra problem": [[31, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem"]], "Rewriting the fitting procedure as a linear algebra problem, more details": [[31, "rewriting-the-fitting-procedure-as-a-linear-algebra-problem-more-details"]], "Ridge Regression": [[33, "ridge-regression"]], "Ridge and LASSO Regression": [[32, "ridge-and-lasso-regression"], [33, "ridge-and-lasso-regression"], [33, "id2"]], "Ridge and Lasso Regression": [[5, null], [5, "id1"]], "SGD example": [[34, "sgd-example"]], "SGD vs Full-Batch GD: Convergence Speed and Memory Comparison": [[34, "sgd-vs-full-batch-gd-convergence-speed-and-memory-comparison"]], "SVD analysis": [[33, "svd-analysis"]], "Same code but now with momentum gradient descent": [[13, "same-code-but-now-with-momentum-gradient-descent"], [34, "same-code-but-now-with-momentum-gradient-descent"], [34, "id3"], [34, "id4"]], "Schedule first week": [[31, "schedule-first-week"]], "Schematic Regression Procedure": [[9, "schematic-regression-procedure"]], "Second moment of the gradient": [[34, "second-moment-of-the-gradient"]], "September 15-19": [[19, "september-15-19"]], "Setting up a Multi-layer perceptron model for classification": [[39, "setting-up-a-multi-layer-perceptron-model-for-classification"]], "Setting up the Back propagation algorithm": [[12, "setting-up-the-back-propagation-algorithm"]], "Setting up the Back propagation algorithm, part 3": [[38, "setting-up-the-back-propagation-algorithm-part-3"], [39, "setting-up-the-back-propagation-algorithm-part-3"]], "Setting up the Matrix to be inverted": [[32, "setting-up-the-matrix-to-be-inverted"], [33, "setting-up-the-matrix-to-be-inverted"]], "Setting up the back propagation algorithm": [[38, "setting-up-the-back-propagation-algorithm"]], "Setting up the back propagation algorithm and algorithm for a feed forward NN, initalizations": [[39, "setting-up-the-back-propagation-algorithm-and-algorithm-for-a-feed-forward-nn-initalizations"]], "Setting up the back propagation algorithm, part 1": [[39, "setting-up-the-back-propagation-algorithm-part-1"]], "Setting up the back propagation algorithm, part 2": [[38, "setting-up-the-back-propagation-algorithm-part-2"], [39, "setting-up-the-back-propagation-algorithm-part-2"]], "Setting up the equations for a neural network": [[38, "setting-up-the-equations-for-a-neural-network"], [39, "setting-up-the-equations-for-a-neural-network"]], "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"], [34, "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": [[32, "simple-case"], [33, "simple-case"]], "Simple code for solving the above problem": [[33, "simple-code-for-solving-the-above-problem"]], "Simple example": [[36, "simple-example"], [38, "simple-example"]], "Simple example code": [[34, "simple-example-code"]], "Simple example to illustrate Ordinary Least Squares, Ridge and Lasso Regression": [[33, "simple-example-to-illustrate-ordinary-least-squares-ridge-and-lasso-regression"]], "Simple geometric interpretation": [[33, "simple-geometric-interpretation"]], "Simple linear regression model using scikit-learn": [[0, "simple-linear-regression-model-using-scikit-learn"], [31, "simple-linear-regression-model-using-scikit-learn"]], "Simple neural network and the back propagation equations": [[38, "simple-neural-network-and-the-back-propagation-equations"], [39, "simple-neural-network-and-the-back-propagation-equations"]], "Simple one-dimensional second-order polynomial": [[18, "simple-one-dimensional-second-order-polynomial"]], "Simple program": [[33, "simple-program"], [34, "simple-program"]], "Simpler examples first, and automatic differentiation": [[38, "simpler-examples-first-and-automatic-differentiation"]], "Slightly different approach": [[34, "slightly-different-approach"]], "Smarter way of evaluating the above function": [[38, "smarter-way-of-evaluating-the-above-function"]], "Sneaking in automatic differentiation using Autograd": [[34, "sneaking-in-automatic-differentiation-using-autograd"]], "Software and needed installations": [[25, "software-and-needed-installations"], [31, "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"]], "Solving using Newton-Raphson\u2019s method": [[36, "solving-using-newton-raphson-s-method"], [37, "solving-using-newton-raphson-s-method"]], "Some famous Matrices": [[24, "some-famous-matrices"]], "Some parallels from real analysis": [[38, "some-parallels-from-real-analysis"]], "Some selected properties": [[36, "some-selected-properties"]], "Some simple problems": [[13, "some-simple-problems"], [33, "some-simple-problems"]], "Some useful matrix and vector expressions": [[32, "some-useful-matrix-and-vector-expressions"]], "Splitting our Data in Training and Test data": [[0, "splitting-our-data-in-training-and-test-data"], [32, "splitting-our-data-in-training-and-test-data"]], "Standard Approach based on the Normal Distribution": [[35, "standard-approach-based-on-the-normal-distribution"]], "Standard steepest descent": [[13, "standard-steepest-descent"]], "Statistical analysis": [[35, "statistical-analysis"], [36, "statistical-analysis"]], "Statistical analysis and optimization of data": [[23, "statistical-analysis-and-optimization-of-data"], [31, "statistical-analysis-and-optimization-of-data"]], "Steepest descent": [[13, "steepest-descent"], [33, "steepest-descent"]], "Stochastic Gradient Descent": [[34, "stochastic-gradient-descent"]], "Stochastic Gradient Descent (SGD)": [[13, "stochastic-gradient-descent-sgd"], [34, "stochastic-gradient-descent-sgd"]], "Stochastic variables and the main concepts, the discrete case": [[28, "stochastic-variables-and-the-main-concepts-the-discrete-case"]], "Strongly Convex Case": [[34, "strongly-convex-case"]], "Suggested readings and videos": [[37, "suggested-readings-and-videos"]], "Summing up": [[35, "summing-up"], [36, "summing-up"]], "Support Vector Machines, overarching aims": [[8, null]], "Synthetic data generation": [[36, "synthetic-data-generation"], [37, "synthetic-data-generation"]], "Systematic reduction": [[3, "systematic-reduction"]], "Teachers": [[31, "teachers"]], "Teachers and Grading": [[29, null]], "Teaching Assistants Fall semester 2023": [[29, "teaching-assistants-fall-semester-2023"]], "Tensorflow": [[39, "tensorflow"]], "Tentative deadllines for projects": [[29, "tentative-deadllines-for-projects"]], "Testing the Means Squared Error as function of Complexity": [[0, "testing-the-means-squared-error-as-function-of-complexity"], [32, "testing-the-means-squared-error-as-function-of-complexity"]], "Testing the XOR gate and other gates": [[39, "testing-the-xor-gate-and-other-gates"]], "Textbooks": [[30, null]], "The back propagation equations for a neural network": [[39, "the-back-propagation-equations-for-a-neural-network"]], "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 Central Limit Theorem": [[35, "the-central-limit-theorem"]], "The Hessian matrix": [[33, "the-hessian-matrix"], [34, "the-hessian-matrix"]], "The Hessian matrix for Ridge Regression": [[33, "the-hessian-matrix-for-ridge-regression"], [34, "the-hessian-matrix-for-ridge-regression"]], "The Jacobian": [[32, "the-jacobian"]], "The MNIST dataset again": [[3, "the-mnist-dataset-again"]], "The Neural Network": [[39, "the-neural-network"]], "The OLS case": [[33, "the-ols-case"]], "The RELU function family": [[1, "the-relu-function-family"], [39, "the-relu-function-family"]], "The Ridge case": [[33, "the-ridge-case"]], "The SVD, a Fantastic Algorithm": [[32, "the-svd-a-fantastic-algorithm"], [33, "the-svd-a-fantastic-algorithm"]], "The Softmax function": [[1, "the-softmax-function"], [39, "the-softmax-function"]], "The \\chi^2 function": [[0, "the-chi-2-function"], [31, "the-chi-2-function"], [31, "id4"], [31, "id5"], [31, "id6"], [31, "id7"], [31, "id8"]], "The approximation theorem in words": [[38, "the-approximation-theorem-in-words"]], "The bias-variance tradeoff": [[6, "the-bias-variance-tradeoff"], [35, "the-bias-variance-tradeoff"], [36, "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": [[32, "the-complete-code-with-a-simple-data-set"]], "The cost function rewritten": [[36, "the-cost-function-rewritten"], [37, "the-cost-function-rewritten"]], "The cost/loss function": [[32, "the-cost-loss-function"]], "The course has two central parts": [[23, "the-course-has-two-central-parts"]], "The derivative of the Logistic funtion": [[39, "the-derivative-of-the-logistic-funtion"]], "The derivative of the cost/loss function": [[33, "the-derivative-of-the-cost-loss-function"], [34, "the-derivative-of-the-cost-loss-function"]], "The derivatives": [[38, "the-derivatives"], [39, "the-derivatives"]], "The equations": [[33, "the-equations"]], "The equations for ordinary least squares": [[32, "the-equations-for-ordinary-least-squares"]], "The equations to solve": [[36, "the-equations-to-solve"], [37, "the-equations-to-solve"]], "The first Case": [[33, "the-first-case"]], "The gradient step": [[34, "the-gradient-step"]], "The ideal": [[33, "the-ideal"]], "The logistic function": [[7, "the-logistic-function"], [36, "the-logistic-function"]], "The mean squared error and its derivative": [[32, "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 optimization problem": [[38, "the-optimization-problem"]], "The ouput layer": [[38, "the-ouput-layer"], [39, "the-ouput-layer"]], "The plethora of machine learning algorithms/methods": [[31, "the-plethora-of-machine-learning-algorithms-methods"]], "The same example but now with cross-validation": [[35, "the-same-example-but-now-with-cross-validation"], [36, "the-same-example-but-now-with-cross-validation"]], "The sensitiveness of the gradient descent": [[33, "the-sensitiveness-of-the-gradient-descent"]], "The singular value decomposition": [[5, "the-singular-value-decomposition"], [32, "the-singular-value-decomposition"], [33, "the-singular-value-decomposition"]], "The training": [[38, "the-training"], [39, "the-training"]], "The two-dimensional case": [[8, "the-two-dimensional-case"]], "Theoretical Convergence Speed and convex optimization": [[34, "theoretical-convergence-speed-and-convex-optimization"]], "Time decay rate": [[34, "time-decay-rate"]], "To our real data: nuclear binding energies. Brief reminder on masses and binding energies": [[31, "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": [[31, "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"], [39, "train-and-test-datasets"]], "Two parameters": [[36, "two-parameters"], [37, "two-parameters"]], "Two-dimensional Objects": [[3, "two-dimensional-objects"]], "Type of problem": [[2, "type-of-problem"]], "Types of Machine Learning": [[31, "types-of-machine-learning"]], "Understanding what happens": [[35, "understanding-what-happens"], [36, "understanding-what-happens"]], "Universal approximation theorem": [[38, "universal-approximation-theorem"]], "Updating the gradients": [[38, "updating-the-gradients"], [39, "updating-the-gradients"]], "Usage of the above learning rate schedulers": [[39, "usage-of-the-above-learning-rate-schedulers"]], "Use the books!": [[19, "use-the-books"]], "Useful Python libraries": [[23, "useful-python-libraries"], [31, "useful-python-libraries"]], "Using Autograd": [[13, "using-autograd"]], "Using Keras": [[39, "using-keras"]], "Using Scikit-learn": [[37, "using-scikit-learn"]], "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"], [33, "using-gradient-descent-methods-limitations"], [34, "using-gradient-descent-methods-limitations"]], "Using the chain rule and summing over all k entries": [[38, "using-the-chain-rule-and-summing-over-all-k-entries"], [39, "using-the-chain-rule-and-summing-over-all-k-entries"]], "Using the correlation matrix": [[37, "using-the-correlation-matrix"]], "Vanishing gradients": [[39, "vanishing-gradients"]], "Various steps in cross-validation": [[35, "various-steps-in-cross-validation"], [36, "various-steps-in-cross-validation"]], "Visualization": [[1, "visualization"], [1, "id1"], [39, "visualization"], [39, "id1"]], "Visualizing the Tree, Classification": [[9, "visualizing-the-tree-classification"]], "Week 34: Introduction to the course, Logistics and Practicalities": [[31, null]], "Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression": [[32, null]], "Week 36: Linear Regression and Gradient descent": [[33, null]], "Week 37: Gradient descent methods": [[34, null]], "Week 38: Statistical analysis, bias-variance tradeoff and resampling methods": [[35, null]], "Week 39: Resampling methods and logistic regression": [[36, null]], "Week 40: Gradient descent methods (continued) and start Neural networks": [[37, null]], "Week 41 Neural networks and constructing a neural network code": [[38, null]], "Week 42 Constructing a Neural Network code with examples": [[39, null]], "Weights and biases": [[39, "weights-and-biases"]], "What Is Generative Modeling?": [[31, "what-is-generative-modeling"]], "What does it mean?": [[32, "what-does-it-mean"], [33, "what-does-it-mean"]], "What is Machine Learning?": [[0, "what-is-machine-learning"]], "What is a good model?": [[0, "what-is-a-good-model"], [31, "what-is-a-good-model"]], "What is a good model? Can we define it?": [[31, "what-is-a-good-model-can-we-define-it"]], "When do we stop?": [[34, "when-do-we-stop"]], "Which activation function should I use?": [[1, "which-activation-function-should-i-use"]], "Which activation function should we use?": [[39, "which-activation-function-should-we-use"]], "Why Combine Momentum and RMSProp?": [[34, "why-combine-momentum-and-rmsprop"]], "Why Linear Regression (aka Ordinary Least Squares and family)": [[31, "why-linear-regression-aka-ordinary-least-squares-and-family"]], "Why multilayer perceptrons?": [[37, "why-multilayer-perceptrons"], [38, "why-multilayer-perceptrons"]], "Why resampling methods": [[35, "why-resampling-methods"]], "Why resampling methods ?": [[35, "id1"], [36, "why-resampling-methods"]], "Wisconsin Cancer Data": [[7, "wisconsin-cancer-data"]], "With Lasso Regression": [[33, "with-lasso-regression"]], "Wrapping it up": [[35, "wrapping-it-up"]], "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": [[33, "writing-the-cost-function"]], "XGBoost: Extreme Gradient Boosting": [[10, "xgboost-extreme-gradient-boosting"]], "Yet another Example": [[33, "yet-another-example"]], "a) Expression for Ridge regression": [[17, "a-expression-for-ridge-regression"]], "scikit-learn implementation": [[1, "scikit-learn-implementation"], [39, "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", "exercisesweek41", "exercisesweek42", "intro", "linalg", "project1", "project2", "schedule", "statistics", "teachers", "textbooks", "week34", "week35", "week36", "week37", "week38", "week39", "week40", "week41", "week42"], "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", "exercisesweek41.ipynb", "exercisesweek42.ipynb", "intro.md", "linalg.ipynb", "project1.ipynb", "project2.ipynb", "schedule.md", "statistics.ipynb", "teachers.md", "textbooks.md", "week34.ipynb", "week35.ipynb", "week36.ipynb", "week37.ipynb", "week38.ipynb", "week39.ipynb", "week40.ipynb", "week41.ipynb", "week42.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, 24, 25, 26, 28, 29, 31, 32, 38, 39], "0": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38], "00": [0, 1, 5, 11, 31, 32, 38, 39], "000": [1, 3, 39], "000000": [], "00000000e": [], "001": [2, 8, 13, 21, 33, 34], "004": 5, "004113634617443131": 32, "004113634617443139": 32, "00411363461744314": 32, "004113634617443147": 32, "005b82": [], "00622f": [], "00727646693": [0, 31], "0072b2": [], "00749c": [], "0076268": 21, "008561": [], "0086649156": [0, 31], "00e0e0": [], "01": [0, 1, 2, 5, 9, 11, 13, 17, 30, 31, 32, 34, 36, 37, 38, 39], "010726": [], "0110": 28, "01719003e": [], "02": [0, 4, 7, 12, 31, 36, 37, 39], "02334824": [], "023b95": [], "024c1a": [], "025": 26, "02857": 4, "02f": 6, "03077640549": 4, "03097597e": [], "031": 5, "04": 11, "0458": 9, "05": [4, 6], "0550ae": [], "05767": 38, "062292565": 4, "062435": [], "06730814": [], "07": [], "0713": [0, 31], "07285": 3, "08": 28, "08078025e": [], "080808": [], "08336233266": 4, "08376632": 32, "083766322923899": 32, "0837663229239043": 32, "0917": 9, "0969da4a": [], "0d1117": [], "0n": [0, 31], "0x113e21950": 17, "1": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 24, 27, 28, 29, 30, 31, 33, 34, 35, 36, 37], "10": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 22, 24, 25, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 39], "100": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 24, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "1000": [0, 1, 2, 4, 5, 8, 11, 13, 14, 18, 19, 21, 23, 26, 28, 31, 33, 34, 36, 37, 39], "10000": [2, 5, 6, 10, 11, 13, 28, 35], "100000": 8, "10001": 10, "1001": 28, "1002": 28, "1003": 28, "1005": 28, "1007": [35, 36], "1009": 28, "101": 16, "1011": 28, "1013": 28, "1013904243": 28, "1015": 28, "102": 16, "1023": 28, "1024": 3, "1026": 28, "1027": 28, "103": [1, 39], "1030": 28, "1037": 28, "1038": 28, "1040": 28, "1047": 28, "107": 16, "108": [], "10e": 39, "10th": 9, "10x": [0, 26, 31], "10y": 26, "11": [0, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "110": [], "1100": 28, "1101": 28, "111": [1, 7, 12, 36, 37, 38, 39], "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, 21, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 37, 39], "120": 3, "121": [8, 9, 10, 16], "1215pm": [29, 31], "122": [8, 9, 10], "124": [0, 31], "125": 16, "127": [4, 16], "128": [3, 4, 13, 34], "129": 16, "1298": 9, "12pm": [29, 31], "13": [0, 2, 9, 12, 22, 24, 26, 28, 31, 37], "131": 16, "133": [7, 36], "135": 16, "136": 16, "14": [0, 2, 4, 6, 8, 9, 10, 12, 24, 26, 28, 30, 32, 35, 36], "141": 16, "1412": 34, "141414": [], "143": 16, "1446729567": 4, "149": 16, "14g": [6, 35], "15": [0, 2, 4, 6, 7, 8, 9, 12, 13, 25, 26, 28, 31, 33, 34, 36, 37], "150": [4, 8, 21, 36, 37], "1502": 38, "152": 16, "153760": [], "156": 16, "157": [], "158": [], "159": 16, "15g": [6, 35], "15pm": 31, "16": [1, 2, 3, 4, 5, 8, 9, 10, 21, 28, 31, 33, 35], "160": 16, "1603": 3, "161": 16, "162": 16, "16231451": 4, "163": 16, "16384": 3, "164": 16, "167": 16, "17": [1, 2, 8, 22, 28, 39], "172": 16, "173": 16, "175": [35, 36], "176": 16, "178": 16, "179": 16, "1797": [1, 39], "18": [2, 6, 7, 8, 9, 10, 28, 31, 35, 36], "1807": 4, "181036": [], "18392847": [], "18c1c4": [], "19": [2, 28, 31, 35], "192": [35, 36], "1940": [], "1943": [12, 37, 38], "19569961": 32, "19680801": [], "1970": [24, 31], "1973": 9, "1979": [6, 35], "1989": 38, "1991": 38, "1_1": [12, 37], "1_2": [12, 37], "1_3": [12, 37], "1cm": [0, 8, 10, 28, 31, 38, 39], "1d": [1, 2, 3, 36, 37, 39], "1e": [2, 4, 13, 14, 34, 36, 37, 39], "1e10": 14, "1e1e1": [], "1e4": 6, "1f": 1, "1ffvbn0xlhv": 22, "1k": 24, "1n": [0, 31], "1x": [0, 31], "1zkibvqf": 21, "2": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 23, 24, 25, 28, 30, 34, 35, 36, 37], "20": [0, 1, 2, 6, 7, 8, 16, 17, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "200": [0, 2, 3, 4, 8, 9, 10, 36, 37], "2000": [0, 32], "2001": [], "2004": [13, 33], "2006": 30, "2007": [], "20072279": [], "2008": [31, 34], "2009": [], "2010": [1, 39], "2011": [1, 34, 39], "2012": 34, "2013": [], "2014": [4, 34], "2015": [1, 39], "2016": [0, 31], "2018": [0, 6, 32, 35, 36], "2019": [], "2020": [], "2021": [6, 14, 32, 34], "2022": [26, 31, 38, 39], "2023": 39, "2024": [21, 35], "2025": [18, 21, 22, 26, 31, 32, 33, 34, 35], "21": [0, 1, 5, 7, 9, 12, 24, 31, 32, 33, 36, 37, 38, 39], "2116753732": 4, "215pm": [29, 31], "2167072": [], "22": [0, 1, 5, 12, 13, 24, 31, 32, 33, 37, 39], "221": 8, "225": 4, "22948497": [], "23": [1, 12, 24, 37, 39], "24": [0, 1, 24, 31, 39], "242424": [], "24292f": [], "25": [2, 3, 4, 5, 6, 8, 9, 11, 32], "250": [2, 4, 7, 9, 36], "25000": [], "250154": [], "252124": [], "253775": [], "255": [3, 26], "256": [4, 34], "25x": [25, 26], "26": [], "26303845": [], "264": [], "265": [], "265109911": 4, "266": [], "269": [], "27": [1, 39], "270": [], "278": [33, 34], "27n_": 28, "28": [1, 3, 4, 39], "283": [33, 34], "2830637392": 4, "2861": 28, "2873": 9, "2882": 28, "2886": 28, "2890": [0, 31], "2892": 28, "29": 32, "2915": 28, "2931": 31, "29364655": [], "294399745619595": [], "296247": [], "2968": 31, "2980": [21, 31], "298273": [], "298375": [], "2990": 31, "2_": [12, 37], "2_1": [12, 37], "2_2": [12, 37], "2_3": [12, 37], "2_i": [12, 37], "2_m": [6, 28, 35], "2_t": 13, "2_x": 28, "2a": 17, "2a1968": [], "2b": 28, "2b2b2b": [], "2c8f433990d1": 34, "2cm": 8, "2d": [1, 3, 11, 12, 23, 31, 36, 37, 38, 39], "2e": [6, 35, 36], "2f": [0, 7, 9, 10, 11, 12, 31, 36, 37], "2g": 2, "2g_i": 2, "2k": 3, "2m": [6, 35], "2mvizaqfst8": 32, "2n": [0, 2, 3, 31, 32], "2nd": 9, "2p": [28, 38], "2pt": 4, "2x": [0, 3, 8, 13, 31, 38], "2x_ix_jy_iy_j": 8, "2x_j": 8, "2xb": 38, "2y_i": 10, "2y_j": 8, "3": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 23, 24, 25, 26, 27, 28, 29, 31, 33, 34, 35, 36, 37], "30": [0, 1, 4, 6, 7, 10, 13, 29, 34, 35, 36, 37, 39], "300": [36, 37], "30000": [0, 31], "3072": 3, "31": [12, 24, 28, 37], "315": [6, 32, 34], "3155": [0, 5, 6, 32, 33, 34, 35, 36], "32": [3, 4, 6, 12, 13, 24, 28, 34, 37], "3200": [1, 39], "3250": [1, 39], "3297": [], "33": [12, 24, 29, 37], "3303": [], "3310": [], "332331": [], "333": [7, 36], "3331": [], "3337": [], "34": 24, "3436": [0, 31], "3437": [0, 31], "35": [0, 6, 25, 31, 33, 34], "3581341341": 4, "359": [5, 33], "36": [0, 5, 6, 18, 25, 28], "37": [25, 33, 35, 36], "370782966": 4, "38": [25, 28], "387": [35, 36], "39": [0, 25, 26, 29, 31], "3d": [2, 3, 4, 6, 13, 16, 35, 36], "3d73a9": [], "3f": [1, 3, 9, 39], "3n": 24, "3x": [2, 8], "3x_0x_1": 38, "3x_i": 2, "3y": 8, "4": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 24, 25, 26, 28, 31, 33, 34, 35, 36, 37, 38], "40": [1, 6, 29, 31, 35, 36, 39], "400": 4, "4000": 31, "40008b9a5380fcacce3976bf7c08af5b": 34, "4050": [30, 31], "41": [24, 26], "4155": [2, 15], "41589548": [], "42": [1, 4, 8, 9, 10, 24, 26, 36, 37, 38], "43": [0, 7, 24], "4310": 31, "436462435": 4, "437a6b": [], "44": [0, 24, 33, 34], "45": [29, 31], "46": [29, 31], "462": [7, 36], "47": [29, 31], "473d18": [], "479465113": 4, "47958494": [], "48": [], "48257387": [29, 31], "49": [5, 6, 11], "49152": 3, "4940954": [0, 31], "4990": 28, "4992": 28, "4997": 28, "4c4b4be8": [], "4c4c7f": [9, 10], "4d": 3, "4f": [6, 26, 36, 37], "4pm": [29, 31], "4y": 8, "4y_i": 10, "5": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "50": [1, 2, 3, 4, 6, 7, 8, 10, 13, 26, 31, 32, 34, 35, 37, 38, 39], "500": [1, 3, 4, 6, 9, 10, 13, 34, 35, 36, 39], "5000": [25, 26], "5018": 28, "506": [], "507d50": [9, 10], "50j": 13, "50x10": [1, 39], "51": 10, "510": [1, 39], "512132": [], "515151": [], "5177783846": 4, "52": 36, "53": [9, 36], "5391cf": [], "54": [6, 28], "5411205": [], "54894451": [], "55": [1, 39], "56": [1, 39], "56469864": 21, "56536": [0, 31], "569": 1, "57": [0, 8, 29, 31], "571": [5, 33], "576": 35, "58": [10, 29, 31], "58a6ff70": [], "591317992": 4, "5ca7e4": [], "5cm": 28, "5f": [8, 34], "5x": [8, 18], "5y": 8, "6": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 18, 24, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 39], "60": [1, 3], "60000": 4, "6019067271": 4, "60610368": 21, "606439": [], "61362": 26, "622cbc": [], "625": [7, 36], "63": [1, 39], "64": [1, 3, 4, 13, 24, 31, 34, 39], "64x50": [1, 39], "65": [1, 8, 9, 39], "66666691": [], "66707b": [], "66ccee": [], "66e9ec": [], "6730c5": [], "6887363571": 4, "69": [16, 28], "69069n_": 28, "691": [], "6980": 34, "6e7681": [], "6e7781": [], "6f98b3": [], "6n_": 28, "7": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 24, 25, 26, 28, 30, 31, 32, 34, 35, 36, 37, 38, 39], "70": [1, 7, 36, 39], "702c00": [], "70653767": 4, "71": [1, 39], "724": 3, "72f088": [], "73": [], "7304881": [], "737373": [], "75": [5, 6, 8, 11, 35], "76": [29, 31, 36], "765": [7, 36], "77": [29, 31], "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, 21, 24, 26, 28, 29, 31, 33, 36, 37, 39], "80": [0, 1, 5, 8, 17, 32, 39], "800": [4, 7, 36], "8045e5": [], "81": [1, 39], "815am": [29, 31], "81b19b": [], "8250df": [], "84858": [35, 36], "85": [1, 39], "8702784034": 4, "8786ac": [], "88": 31, "8a4600": [], "8b949e": [], "8c8c8c": [], "8f": [6, 35, 36], "8g": [6, 35], "8n": 24, "8x8": [1, 39], "9": [0, 1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 24, 28, 31, 34, 36, 37, 39], "90": 1, "9040": 9, "91": [29, 31], "912583": [], "91cbff": [], "92": [29, 31], "93": 16, "931": [0, 31], "933": [5, 33], "937": 28, "938": 28, "939": [0, 28, 31], "94": 28, "95": [1, 11, 35, 39], "953800": [], "954": 28, "955820c21e8b": 4, "9579870417283": 21, "96": [6, 35], "960": 28, "961": 28, "962": 28, "9649652536": 4, "96611194e": [], "974eb7": [], "978": [35, 36], "9780387310732": 30, "9780387848570": 30, "9781098134174": 31, "9781492032632": 30, "9781801819312": 31, "97898392": 32, "98": [0, 1, 16, 39], "985": 28, "986": 28, "98661b": [], "989": 28, "9898ff": [9, 10], "99": [13, 16, 34, 35], "991": 28, "992": 28, "993": 28, "996": 5, "996b00": [], "999": [9, 28, 34, 39], "999999": [], "9e86c8": [], "9e8741": [], "9f4e55": [], "9x": 6, "9y": 6, "A": [2, 3, 5, 6, 7, 10, 11, 12, 13, 15, 16, 19, 20, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 34, 38], "AND": 2, "AS": [], "AT": [], "And": [0, 3, 4, 5, 6, 9, 13, 20, 22, 23, 25, 26, 28, 33], "As": [0, 1, 2, 3, 4, 5, 6, 8, 10, 12, 13, 15, 16, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "At": [0, 4, 6, 13, 20, 31, 34], "BE": [0, 31], "BUT": [], "BY": [], "Be": [2, 18, 23, 31], "Being": 13, "But": [0, 1, 2, 3, 5, 6, 9, 10, 16, 21, 26, 28, 32, 35, 36, 39], "By": [0, 3, 5, 6, 12, 13, 17, 19, 24, 31, 32, 33, 34, 35, 37], "FOR": [], "For": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 19, 21, 22, 23, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "IF": [6, 32, 34], "IN": 30, "If": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 18, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "In": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 39], "Ising": [5, 12, 32, 33, 37, 38], "It": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 20, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "Its": [1, 2, 4, 11, 39], "NO": [], "NOT": [], "No": [6, 9, 31, 32, 34, 37, 39], "Not": [0, 1, 5, 6, 32, 33, 34, 35, 37, 39], "OF": [], "ON": [], "OR": 28, "Of": 28, "On": [0, 3, 25, 28, 29, 30, 31, 34, 35], "One": [0, 1, 3, 4, 5, 6, 7, 8, 11, 12, 13, 17, 28, 32, 33, 34, 35, 36, 37, 38, 39], "Or": [0, 1, 6, 31, 39], "SUCH": [], "Such": [0, 6, 12, 16, 28, 34, 35, 36, 37, 38, 39], "THE": [], "TO": 39, "That": [0, 5, 7, 10, 11, 12, 14, 25, 26, 28, 31, 35, 36, 37, 38, 39], "The": [4, 10, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 30], "Then": [0, 1, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 24, 31, 33, 34, 35, 38, 39], "There": [0, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 24, 25, 26, 28, 29, 31, 32, 33, 34, 37, 38], "These": [0, 3, 4, 5, 8, 9, 10, 11, 12, 13, 14, 17, 18, 22, 24, 25, 26, 28, 29, 31, 32, 33, 34, 38, 39], "To": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 24, 26, 28, 32, 33, 34, 35, 36, 37, 38, 39], "WITH": [], "Will": [36, 37], "With": [0, 5, 6, 8, 9, 10, 11, 12, 14, 16, 19, 21, 24, 25, 26, 28, 31, 32, 35, 36, 37, 38, 39], "_": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 24, 25, 31, 32, 33, 34, 35, 36, 37, 39], "_0": [5, 8, 10, 11, 13, 32, 33], "_1": [2, 5, 6, 8, 10, 11, 12, 13, 14, 24, 32, 33, 34, 38, 39], "_2": [2, 5, 8, 11, 12, 13, 24, 32, 34, 37], "_3": 24, "_4": 24, "_9": [13, 34], "__array_finalize__": [], "__class__": [10, 39], "__doc__": [6, 35, 36], "__future__": [8, 9, 38], "__getattribute__": [], "__import__": [], "__init__": [1, 22, 36, 37, 39], "__main__": 2, "__name__": [2, 10, 39], "__new__": [], "__path__": [], "_accuraci": 39, "_add_intercept": [36, 37], "_auto1": [2, 3, 4, 5, 6, 7, 12, 13, 24, 28, 32, 33, 36, 37, 38, 39], "_auto10": [6, 12], "_auto11": 6, "_auto12": 6, "_auto2": [2, 3, 4, 5, 6, 12, 13, 24, 28, 37, 38, 39], "_auto3": [3, 4, 5, 6, 12, 13, 24, 37, 38, 39], "_auto4": [4, 6, 12, 13, 24, 37], "_auto5": [4, 6, 12, 13, 24, 37], "_auto6": [4, 6, 12, 24, 37], "_auto7": [4, 6, 12, 24, 37], "_auto8": [6, 12], "_auto9": [6, 12], "_backpropag": 39, "_build": [0, 23, 25, 26, 30, 31, 39], "_c": [1, 39], "_center": [], "_compile_transl": [], "_compon": 11, "_da": 22, "_data": [], "_depth": 9, "_export": [15, 16, 19], "_feed_forward_sav": 22, "_feedforward": 39, "_format": 39, "_fraction": 9, "_i": [0, 1, 2, 5, 6, 7, 8, 11, 12, 13, 19, 25, 31, 32, 33, 34, 35, 36, 37, 38, 39], "_j": [0, 1, 2, 3, 5, 6, 8, 13, 19, 25, 32, 33, 34, 35, 36, 39], "_k": [13, 33, 34, 39], "_l": [12, 37, 38, 39], "_lambda": 6, "_leaf": 9, "_m": 10, "_mask": [], "_multilayer_perceptron": [], "_n": [2, 5, 8, 11, 13, 32, 33, 34], "_node": 9, "_norm": [], "_p": [5, 8, 32, 33], "_parse_numpydoc_see_also_sect": [], "_progress_bar": 39, "_pydevd_bundl": [], "_ratio": 11, "_sampl": 9, "_set_classif": 39, "_sigmoid": [36, 37], "_softmax": [36, 37], "_split": [6, 9, 25], "_t": [13, 34], "_test": [6, 25], "_varianc": 11, "_weight": 9, "a0": 3, "a0111f": [], "a0faa0": [9, 10], "a1": [0, 21, 22, 31], "a11": [], "a12236": [], "a2": [0, 21, 22, 31], "a25e53": [], "a2bffc": [], "a3": [0, 31], "a4": [0, 31], "a5d6ff": [], "a_": [0, 1, 16, 24, 31, 32, 38, 39], "a_0": [0, 31, 38, 39], "a_1": [38, 39], "a_1a": [0, 31], "a_2": [38, 39], "a_2a": [0, 31], "a_3": [0, 31], "a_3a": [0, 31], "a_4": [0, 31], "a_4a": [0, 31], "a_h": [1, 39], "a_i": [0, 1, 2, 12, 31, 38, 39], "a_j": [1, 12, 38, 39], "a_k": [0, 1, 12, 38, 39], "a_matric": 39, "aa": [], "aaa": [], "aaron": 30, "ab": [0, 2, 5, 13, 14, 31, 32, 34, 38], "ab6369": [], "ab_channel": [23, 37, 38, 39], "abandon": [1, 39], "abe338": [], "abid": 28, "abil": [0, 10], "abl": [0, 1, 4, 5, 6, 7, 10, 12, 13, 16, 18, 20, 21, 25, 32, 33, 34, 36, 37, 38, 39], "about": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 19, 20, 22, 23, 24, 25, 29, 34, 35, 36, 37, 39], "abov": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 26, 28, 30, 31, 32, 34, 35, 36, 37], "abovement": [6, 25, 31, 35, 36], "abscissa": [13, 33], "absent": 34, "absolut": [0, 2, 5, 6, 13, 31, 32, 33, 35, 36], "absorb": [32, 33], "abstract": [1, 34, 36, 39], "abund": 34, "ac": [], "acc_bin": [36, 37], "acc_multi": [36, 37], "acceler": [13, 34], "accept": [0, 3, 6, 9, 21, 25, 32, 34], "access": [3, 11, 28, 31, 34], "accid": [4, 6, 35, 36], "accompani": [0, 31, 32], "accomplish": [8, 9, 13, 34], "accord": [0, 1, 2, 5, 6, 9, 12, 13, 14, 28, 31, 33, 34, 35, 37, 38, 39], "accordingli": 11, "account": [0, 3, 5, 13, 15, 16, 20, 28, 31, 34], "accumul": [12, 13, 28, 34, 37, 38, 39], "accur": [0, 3, 4, 6, 10, 13, 34, 35, 36], "accuraci": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 21, 26, 31, 32, 33, 36, 37, 38, 39], "accuracy_scor": [0, 1, 10, 21, 22, 26, 31, 36, 37, 39], "accuracy_score_numpi": [1, 39], "acheiv": 21, "achiev": [0, 1, 5, 6, 8, 12, 24, 31, 34, 35, 36, 37, 38, 39], "aco": 28, "acquaint": 23, "acquir": [1, 23, 31, 39], "acr": [], "across": [1, 3, 6, 9, 17, 23, 31, 35, 39], "act": [1, 3, 24, 34, 39], "act_func": 39, "act_func_deriv": 39, "actic": 21, "action": 28, "activ": [0, 2, 3, 4, 9, 15, 22, 27, 29, 31, 34], "activation_d": 22, "activation_func": [21, 22], "activest": [], "actual": [0, 1, 4, 5, 6, 8, 11, 15, 16, 18, 21, 24, 28, 31, 32, 33, 34, 35, 39], "ad": [1, 3, 4, 5, 8, 13, 15, 16, 24, 33, 34, 35, 36], "ada_clf": 10, "adaboostclassifi": 10, "adadelta": [13, 34], "adagrad": [25, 35, 38, 39], "adagradmomentum": 39, "adam": [1, 3, 4, 21, 25, 26, 31, 35, 38, 39], "adam_schedul": 39, "adap": 38, "adapt": [4, 6, 13, 17, 30, 33, 35, 36, 38], "add": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 15, 16, 17, 18, 20, 21, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "add6ff": [], "add_": [], "add_subplot": [1, 7, 12, 14, 36, 37, 39], "addendum": 5, "addeventlisten": [], "addit": [0, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 15, 21, 23, 24, 25, 26, 28, 29, 30, 31, 32, 35, 36, 37, 38, 39], "addition": [12, 13, 33, 34, 37, 38], "address": [1, 9, 11, 13, 31, 34, 39], "adjac": [3, 12, 37, 38], "adjoint": [5, 32], "adjust": [0, 5, 12, 13, 33, 34, 37], "admir": [0, 31], "advanc": [4, 6, 12, 30, 31, 34, 35, 36, 37, 38], "advantag": [1, 3, 5, 6, 10, 13, 19, 24, 33, 34, 35, 36, 39], "adversari": 31, "advis": [], "afecionado": 31, "affect": [3, 15, 19, 39], "affin": [0, 3, 8, 11, 32, 38], "afford": 3, "aficionado": 31, "aforement": 14, "african": [], "after": [0, 1, 2, 4, 5, 6, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 38, 39], "afterward": [0, 31], "ag": [0, 7, 31, 32, 36], "ag_0": 2, "again": [0, 1, 4, 5, 6, 7, 8, 10, 11, 12, 13, 25, 26, 28, 31, 32, 33, 35, 36, 37, 38, 39], "against": [1, 4, 7, 10, 36, 39], "agegroup": [7, 36], "agegroupmean": [7, 36], "aggreg": [9, 10, 34], "agorithm": 10, "agre": [5, 6, 28, 32, 33, 34, 35], "agreement": [13, 34], "ahead": 9, "ai": [0, 30], "aid": [11, 20, 34], "aim": [0, 1, 4, 6, 7, 11, 14, 16, 17, 19, 20, 23, 24, 25, 26, 32, 35, 36, 37, 38, 39], "ainv": 5, "airplan": 3, "aka": [5, 26], "al": [0, 2, 4, 16, 17, 20, 26, 30, 31, 32, 33, 35, 36, 37, 38, 39], "alarm": [5, 7], "aldo": 32, "algebra": [0, 3, 5, 13, 23, 32, 33, 35], "algorithm": [0, 1, 2, 4, 5, 6, 7, 8, 13, 14, 16, 23, 24, 25, 28, 30, 35, 36, 37], "align": [0, 2, 5, 6, 7, 8, 13, 28, 31, 32, 33, 35, 36, 37], "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, 32, 33, 34, 35, 36, 37], "allclos": 21, "allevi": [1, 13, 33, 39], "alloc": [3, 24], "allow": [0, 1, 2, 3, 5, 6, 8, 10, 13, 15, 23, 24, 25, 31, 32, 33, 34, 35, 36, 37, 38, 39], "almost": [0, 1, 6, 8, 11, 13, 28, 33, 34, 35, 36, 37, 39], "alon": [2, 9, 34], "along": [2, 3, 4, 5, 6, 9, 10, 11, 15, 20, 21, 22, 23, 24, 31, 32, 33, 35, 36, 39], "alpha": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 14, 28, 31, 32, 33, 34, 35, 36, 37, 39], "alpha_": [10, 34], "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, 22, 23, 24, 28, 31, 32, 33, 36, 37, 38], "also": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "alter": [1, 39], "altern": [0, 1, 4, 5, 6, 8, 9, 11, 13, 15, 18, 24, 25, 31, 32, 34, 35, 36, 39], "although": [0, 1, 5, 6, 8, 10, 13, 16, 19, 20, 31, 34, 35, 36, 38, 39], "alwai": [0, 3, 5, 6, 12, 13, 16, 19, 21, 22, 25, 26, 28, 31, 32, 33, 34, 35, 37, 38], "am": 4, "ambit": [38, 39], "ame2016": [0, 31], "american": [], "amjith": [], "among": [0, 3, 5, 9, 10, 12, 24, 31, 32, 37, 38], "amongst": [5, 35], "amount": [0, 1, 3, 4, 6, 8, 10, 14, 23, 35, 36, 38, 39], "an": [1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 32, 33, 34, 35, 36, 37, 39], "an_": 28, "anaconda": [0, 1, 23, 25, 31, 39], "analogi": 13, "analys": [6, 35, 36], "analysi": [1, 3, 4, 7, 14, 19, 24, 30, 34, 37, 39], "analyt": [2, 3, 5, 6, 7, 12, 13, 17, 22, 23, 25, 31, 32, 33, 34, 35, 36, 37, 38], "analyz": [0, 1, 3, 4, 5, 6, 16, 25, 26, 28, 32, 33, 34], "andrew": [1, 39], "angl": [0, 3, 9, 32, 34], "anharmon": 3, "ani": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14, 15, 16, 19, 21, 28, 31, 32, 34, 35, 38, 39], "anim": [4, 12, 37, 38], "ann": [12, 37, 38], "annot": [0, 1, 3, 7, 8, 31, 37, 39], "announc": 31, "anom": [], "anomali": [], "anonym": 18, "anoth": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 24, 25, 26, 28, 31, 32, 34, 38, 39], "ansatz": [0, 18, 31], "answer": [0, 1, 3, 5, 6, 19, 22, 24, 25, 26, 29, 31, 35, 39], "antialias": [2, 6], "anticip": 4, "anymor": [1, 8, 39], "anyon": [4, 8, 15], "anyth": [1, 15, 16, 21, 22, 28, 39], "anytim": [29, 31], "anywai": [], "apach": [1, 39], "apart": [11, 13, 33, 34], "api": [1, 23, 31, 39], "appar": 2, "appear": [0, 1, 3, 13, 24, 28, 38, 39], "append": [1, 3, 4, 8, 9, 13, 19, 21, 22, 31, 34, 36, 37, 39], "appendic": [25, 26], "appendix": 25, "appli": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 18, 25, 26, 28, 30, 31, 32, 34, 35, 36, 37, 38, 39], "applic": [0, 1, 3, 4, 5, 6, 7, 9, 12, 13, 16, 24, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "apply_gradi": 4, "approach": [1, 2, 4, 5, 6, 9, 10, 11, 12, 13, 15, 16, 18, 21, 23, 25, 28, 30, 32, 33, 38, 39], "approch": 25, "appropri": [2, 6, 9, 12, 13, 17, 23, 28, 34, 35, 36, 37], "approv": 31, "approx": [0, 2, 3, 6, 10, 11, 13, 18, 25, 28, 31, 33, 34, 35], "approxim": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11, 13, 19, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 39], "apt": [0, 23, 25, 31], "aq": 28, "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, 32, 33, 34, 35, 36, 37, 38, 39], "aragorn": 31, "arang": [1, 3, 4, 6, 7, 9, 10, 12, 13, 31, 34, 36, 37, 39], "arbitrari": [1, 4, 6, 8, 12, 13, 28, 33, 35, 37, 38, 39], "arbitrarili": [0, 1, 11, 31, 34, 39], "arc": 6, "architectur": [3, 4, 12, 26, 38], "archiv": [25, 26], "area": [0, 3, 6, 30, 31], "argmax": [1, 11, 21, 36, 37, 39], "argmin": [4, 10, 14], "argsort": 11, "argu": [1, 13, 39], "arguement": 19, "argument": [0, 2, 3, 5, 11, 12, 13, 17, 21, 31, 32, 34, 35, 37, 38, 39], "aris": [0, 6, 12, 13, 28, 31, 33, 35, 36], "arithmet": [0, 13, 24, 31], "arm": [6, 32, 34], "armadillo": 24, "armin": [], "arnulf": [38, 39], "around": [0, 1, 4, 5, 6, 11, 18, 21, 22, 25, 26, 28, 31, 35, 36, 37, 38, 39], "arrai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13, 14, 16, 18, 21, 23, 25, 28, 32, 33, 34, 35, 36, 37, 38, 39], "arrang": [3, 31], "array_equ": [36, 37], "arraybox": 13, "arriv": [0, 6, 9, 11, 19, 24, 28, 31, 35], "arrow": [12, 37, 38, 39], "arrowprop": 8, "art": [0, 1, 23, 39], "articl": [0, 3, 4, 6, 10, 19, 26, 31, 32, 33, 34, 35, 36], "artifici": [0, 2, 7, 12, 30, 31, 36], "artificialneuron": [12, 37, 38], "arug": 13, "arxiv": [3, 4, 34, 38], "as_fram": 26, "asarrai": [0, 6, 9, 32, 34], "asid": 32, "ask": [5, 6, 11, 12, 15, 19, 25, 26, 35, 38, 39], "aspect": [0, 6, 23, 31, 32, 38, 39], "assembl": 3, "assembli": [0, 31], "assert": [4, 39], "assess": [0, 6, 25, 31, 32, 35, 36], "asset": [], "assici": 4, "assign": [0, 7, 8, 9, 12, 13, 14, 15, 27, 29, 30, 31, 36, 37, 39], "associ": [0, 6, 9, 12, 14, 28, 31, 35, 36, 37, 38], "assum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "assumpt": [0, 3, 5, 6, 9, 11, 28, 31, 32, 36], "ast": [0, 5, 6, 31, 35], "astyp": [4, 9, 10, 36, 37], "asymmetri": [0, 31], "asymptot": [4, 6, 34, 35, 36], "atom": [0, 31], "attain": 34, "attempt": [0, 4, 6, 7, 8, 10, 31, 32, 34, 36, 38, 39], "attend": 31, "attent": [0, 24, 31], "attract": [0, 10, 31], "attribut": [0, 9, 22, 31, 39], "audi": [0, 31], "audio": [3, 4], "august": [31, 32], "aurelien": [0, 30, 31], "austfjel": 6, "auth": 15, "authent": 15, "author": [0, 1, 10, 28, 39], "authour": 31, "auto": [9, 10, 26, 28, 39], "auto_exampl": [21, 25, 32], "autocor": 28, "autocorrelation_tim": 28, "autocorrelform": 28, "autocovari": 28, "autoencod": [4, 23, 31], "autoencond": 23, "autograd": [21, 23, 26, 31, 38, 39], "autograd_compliant_predict": 22, "autograd_gradi": 22, "autograd_one_lay": 22, "autom": [0, 23, 30, 31], "automac": 24, "automag": 31, "automat": [0, 1, 2, 3, 4, 11, 16, 21, 22, 23, 24, 26, 31, 37, 39], "automobil": 3, "autonom": 4, "avail": [0, 1, 4, 6, 10, 11, 23, 24, 25, 26, 27, 29, 30, 31, 35, 36, 39], "avali": [20, 25, 26], "averag": [0, 1, 3, 6, 9, 10, 13, 14, 28, 29, 31, 32, 35, 36, 39], "avoid": [0, 4, 5, 6, 9, 11, 13, 18, 21, 24, 32, 34, 35, 36, 39], "awai": [2, 3, 6, 32, 34, 38], "awar": [2, 10], "award": [29, 31], "ax": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 21, 24, 25, 26, 31, 35, 36, 37, 39], "axes3d": [2, 6, 13, 33, 34], "axes_grid1": 6, "axhlin": 8, "axi": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 18, 21, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "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, 21, 22, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "b1": [8, 21, 22], "b19db4": [], "b1bac4": [], "b2": [8, 21, 22], "b3": 8, "b35900": [], "b89784": [], "b_": [0, 1, 24, 38, 39], "b_0": [0, 38], "b_1": [0, 2, 12, 13, 34, 37, 38, 39], "b_2": [0, 13, 38, 39], "b_5": [13, 34], "b_g": [21, 22], "b_group": 9, "b_i": [0, 1, 2, 12, 31, 37, 38, 39], "b_ia_": [0, 31], "b_ia_i": 0, "b_index": 9, "b_j": [1, 12, 37, 38, 39], "b_k": [0, 1, 12, 13, 34, 37, 38, 39], "b_m": [12, 37], "b_score": 9, "b_valu": 9, "ba": 34, "babcock": 31, "bach": 34, "bachelor": [27, 29], "back": [0, 3, 4, 5, 6, 8, 9, 10, 15, 16, 21, 24, 26, 28, 31, 34], "backbon": 24, "backend": [1, 4, 39], "background": [30, 31, 39], "backprogag": 22, "backpropag": [1, 21, 34, 38, 39], "backpropog": 22, "backslash": [], "backtrack": 9, "backup": 24, "backward": [1, 2, 4, 12, 22, 24, 34, 38, 39], "bad": [6, 17, 32, 39], "badli": 28, "bag": [9, 23, 31], "bag_clf": 10, "baggin": 31, "baggingboot": 10, "baggingclassifi": 10, "baggingtre": 10, "bailei": [], "balanc": [6, 34, 35, 36], "ballpark": 18, "band": 24, "bandwidth": 24, "banner": [], "bar": [0, 6, 11, 25, 31, 39], "barber": 30, "bare": [4, 10], "base": [0, 1, 3, 4, 5, 7, 8, 9, 10, 14, 15, 16, 17, 23, 28, 29, 30, 31, 32, 33, 36, 37, 38, 39], "basi": [5, 7, 8, 10, 11, 12, 13, 24, 32, 33, 36, 37, 38], "basic": [6, 8, 12, 13, 14, 15, 23, 25, 28, 31, 35, 39], "basin": 34, "batch": [3, 4, 11, 12, 13, 21, 33, 36, 37], "batch_shap": 4, "batch_siz": [1, 3, 4, 39], "batchnorm": 4, "bay": [7, 36, 37], "baydin": 38, "bayesian": [5, 23, 30, 31], "bbbbbb": [], "beauti": [], "becam": [], "becaus": [0, 1, 2, 3, 4, 5, 6, 8, 9, 12, 13, 14, 31, 32, 33, 34, 35, 36, 37, 39], "becom": [0, 1, 2, 5, 6, 7, 9, 12, 13, 19, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "been": [0, 1, 2, 3, 4, 5, 6, 11, 12, 13, 19, 20, 23, 24, 25, 26, 31, 32, 34, 35, 37, 38, 39], "befor": [0, 1, 2, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 24, 25, 28, 31, 32, 34, 35, 36, 37, 38, 39], "beforehand": [0, 28, 31], "began": [], "begin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 22, 24, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "behav": [1, 6, 13, 33, 35, 36, 39], "behavior": [0, 1, 13, 31, 33, 34, 39], "behaviour": [12, 34, 37, 38, 39], "behind": [0, 1, 6, 8, 13, 31, 33, 39], "being": [0, 1, 2, 3, 4, 5, 7, 8, 10, 11, 12, 13, 17, 20, 28, 31, 32, 33, 34, 36, 37, 38, 39], "believ": [9, 24], "belong": [7, 8, 9, 13, 14, 33, 36, 37, 39], "below": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 18, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "benchmark": 10, "benefici": [1, 13, 39], "benefit": [0, 1, 4, 11, 13, 23, 31, 33, 34, 39], "bengio": [1, 26, 30, 31, 32, 34], "benign": [1, 7, 37], "benno": [38, 39], "berner": [38, 39], "besid": [4, 5, 33], "bessel": [5, 32, 35], "best": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 18, 21, 26, 29, 31, 32, 33, 34, 35, 36, 37, 39], "beta": [1, 3, 10, 11, 13, 16, 17, 19, 31, 32, 33, 39], "beta1": [], "beta2": [], "beta_": [3, 13, 17, 32], "beta_0": [1, 3, 13, 32, 39], "beta_1": [1, 3, 10, 13, 32, 34, 39], "beta_1m_": 34, "beta_1x_i": 13, "beta_2": [3, 13, 34], "beta_2v_": 34, "beta_3": 3, "beta_i": [3, 34], "beta_j": [13, 32], "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, 22, 31, 32, 34, 35, 39], "between": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "beyond": [0, 1, 5, 6, 8, 13, 31, 32, 33, 34, 39], "bf": [13, 14, 24, 28, 33], "bf5400": [], "bg": 31, "bgd": [13, 34], "bia": [0, 1, 2, 3, 5, 8, 9, 10, 12, 13, 20, 21, 22, 26, 31, 32, 33, 37, 38, 39], "bias": [1, 2, 3, 5, 6, 9, 12, 19, 21, 22, 26, 34, 35, 37], "bib": [], "bibliographi": [25, 26], "bibtex": [], "big": [0, 1, 2, 5, 6, 14, 19, 34, 35, 39], "bigger": [1, 6, 32, 39], "bigr": [12, 37], "bike": 9, "bilbo": 31, "billion": [3, 12, 23, 34, 37, 38], "bin": [7, 28, 37], "binari": [0, 3, 5, 7, 9, 10, 12, 26, 31, 36, 37], "binary_cross_entropi": [36, 37], "binary_result": [36, 37], "binarycrossentropi": 4, "bind": 0, "binomi": [23, 28, 31], "binsboot": [6, 35], "bioinformat": 0, "biolog": [1, 12, 37, 38, 39], "bios1100": [23, 31], "bird": [0, 3], "birth": 31, "bishop": [30, 31], "bit": [1, 4, 19, 21, 24, 28, 31, 39], "bitwis": 28, "bivari": 2, "bk": [13, 34], "bla": [24, 31], "black": [8, 9, 14], "blame": [], "block": [6, 10, 23, 24, 28, 31, 35, 36], "blockquot": [], "blog": [26, 31], "blogpost": 4, "blue": [0, 3], "bm": [], "bmatrix": [0, 1, 3, 5, 7, 8, 11, 13, 24, 31, 32, 33, 34, 36, 37, 38, 39], "bmi": [1, 39], "bodi": [0, 1, 4, 12, 37, 38, 39], "bold": 1, "boldfac": [0, 5, 16, 32, 33], "boldsymbol": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 25, 31, 33, 34, 36, 37, 38, 39], "boltzmann": [12, 23, 31, 37, 38], "book": [17, 25, 26, 30, 31, 32, 35, 36], "book1": 30, "bool": [], "boolean": [4, 17], "boost": [1, 9, 23, 31, 39], "boostrap": 10, "bootstrap": [1, 13, 19, 23, 25, 31, 34, 39], "born": 34, "borrow": 31, "boston_dataset": [], "bot": 8, "both": [0, 1, 4, 5, 6, 8, 9, 10, 13, 14, 15, 16, 17, 19, 23, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 39], "bottl": [7, 36, 37], "bottou": 34, "bound": [8, 12, 34, 37, 38, 39], "boundari": [2, 4, 8, 11, 12], "bousquet": 34, "bower": [], "box": [4, 9, 21, 22], "boyd": [8, 13, 33], "bracket": [4, 28], "brain": [1, 7, 12, 36, 37, 38, 39], "branch": [9, 31], "break": [0, 4, 6, 11, 14, 31, 34], "breast": [5, 7, 11, 37], "breviti": 13, "brew": [0, 23, 25, 31], "brg": 8, "brian": [], "brief": [25, 26, 32], "briefli": [0, 16, 19, 31, 35], "bring": [0, 5, 6, 10, 26, 32, 34], "britt": [29, 31], "broad": 0, "broadcast": 21, "broadli": 31, "brought": [13, 23, 31], "brownle": 4, "browser": [15, 31], "brute": [3, 5, 11, 32, 38], "bsd": [], "budget": 34, "buffer_s": 4, "bug": [], "bugfix": [], "bui": 4, "build": [0, 4, 5, 6, 10, 16, 22, 24, 28, 31, 35, 36, 37, 38], "built": [1, 3, 4, 6, 35, 36, 39], "bunch": 11, "bundl": [], "busi": [], "bxe2t": [37, 38, 39], "byte": [24, 31], "c": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 38, 39], "c1": [8, 11], "c2": [8, 11], "c4a2f5": [], "c5e478": [], "c9d1d9": [], "c_": [8, 9, 10, 13, 28, 33, 34], "c_0": 28, "c_1": [12, 37], "c_2": [12, 37], "c_3": [12, 37], "c_4": [12, 37], "c_i": [12, 13, 34, 37], "c_k": 28, "ca": [1, 31], "caab6d": [], "cach": 10, "cal": [0, 8, 10, 12, 13, 33, 34, 38, 39], "calcul": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 16, 19, 22, 24, 26, 28, 31, 34, 35, 36, 37, 38, 39], "california": [25, 26], "call": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 21, 23, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "callabl": 39, "calor": [0, 32], "caltech": [], "cambridg": [13, 30, 33, 38, 39], "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, 24, 25, 26, 28, 29, 30, 32, 33, 37, 39], "cancel": [0, 13, 31, 32], "cancer": [5, 10, 37], "cancerpd": [7, 37], "candid": [8, 9, 10, 34], "cannot": [0, 1, 4, 5, 6, 7, 8, 9, 25, 28, 32, 33, 34, 37, 39], "canopi": [0, 23, 25, 31], "canva": [15, 16, 19, 20, 25, 26, 31], "cap": 5, "capabl": [0, 1, 8, 13, 23, 31], "capac": [2, 29], "capita": [], "caption": [20, 25, 26], "captur": [4, 11, 12, 31, 37, 38], "car": [3, 4], "card": [0, 7, 31, 36, 37], "cardin": [1, 39], "care": [11, 15, 19, 22, 34], "carefulli": [13, 34], "carlo": [0, 6, 23, 28, 30, 31, 35, 36], "carri": [2, 6, 7, 25, 35, 36, 37], "cart": 10, "case": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 13, 14, 15, 16, 23, 24, 25, 26, 31, 35, 38, 39], "casella": 30, "cast": [1, 39], "cat": [3, 4], "catch": 0, "categor": [0, 1, 3, 9, 11, 31, 36, 37, 39], "categori": [0, 1, 3, 7, 10, 12, 14, 31, 36, 37, 38, 39], "categorical_cross_entropi": [36, 37], "categorical_crossentropi": [1, 3, 39], "caus": [0, 5, 6, 28, 31, 32, 33, 34, 35, 36], "causal": 0, "causat": [0, 31], "cax": 1, "cb": [6, 31], "cbar": 1, "cc": [0, 1, 5, 13, 31, 32, 33, 34, 38, 39], "cc398b": [], "ccbb44": [], "ccc": [5, 12, 33, 37], "cdf": 28, "cdot": [0, 2, 6, 12, 13, 14, 24, 28, 31, 33, 34, 35, 37], "celebr": [13, 33], "cell": [4, 21, 22], "center": [0, 1, 6, 7, 8, 9, 11, 14, 18, 25, 28, 31, 32, 34, 35, 36, 37, 39], "central": [0, 3, 5, 6, 8, 16, 20, 24, 26, 31, 32, 38, 39], "centroid": [14, 28], "centroid_differ": 14, "centuri": 3, "certain": [0, 3, 6, 7, 9, 21, 28, 31, 32, 35, 36, 37], "certainti": 35, "cf": [], "cf222e": [], "cffi": [], "cg": 13, "cha": [], "chain": [0, 1, 13, 22, 23, 28, 31], "challeng": [15, 38], "chanc": [1, 5, 13, 28, 34, 39], "chang": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 19, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "changelog": [], "channel": 3, "chap4": [38, 39], "chapter": [0, 6, 10, 11, 16, 17, 19, 24, 25, 26, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "chapter3": [0, 25], "charact": [0, 3, 5, 31, 32, 33], "character": [8, 9, 10, 12, 28, 37, 39], "characterist": [0, 1, 3, 10, 13, 31, 39], "charg": [0, 31], "charl": [], "charset": [], "chase": 4, "chatgpt": [15, 25, 26], "chd": [7, 36], "chddata": [7, 36], "cheap": [5, 32, 33, 34], "cheaper": [1, 13, 34, 39], "check": [1, 3, 4, 5, 11, 13, 15, 16, 19, 21, 22, 24, 31, 34, 36, 37, 39], "checkmark": 3, "checkpoint": 4, "checkpoint_dir": 4, "checkpoint_prefix": 4, "chen": 10, "cheng": 32, "chiaramont": 2, "childcar": 16, "children": 16, "choic": [0, 1, 2, 3, 4, 6, 9, 12, 13, 14, 20, 24, 31, 32, 33, 34, 35, 36, 37], "choleski": [5, 24, 32, 33], "choos": [2, 3, 6, 9, 10, 11, 13, 14, 15, 18, 19, 21, 25, 26, 33, 35, 36, 37], "chosen": [0, 1, 2, 6, 8, 9, 10, 13, 16, 28, 31, 33, 34, 35, 36, 39], "chosen_datapoint": [1, 39], "christian": 30, "christoph": [30, 31], "chunk": 34, "cifar": 3, "cifar10": 3, "circ": [1, 12, 34, 38, 39], "circl": [0, 8, 12, 32, 34, 37, 38], "circuit": 3, "circumfer": 9, "circumv": [1, 5, 13, 32, 33, 34, 39], "citat": [], "cite": [20, 25, 26], "ckpt": 4, "cl": [36, 37], "claim": [], "clarifi": 21, "clariti": 28, "class": [0, 1, 3, 4, 6, 7, 8, 9, 11, 12, 13, 21, 22, 28, 31, 35, 39], "class0": [36, 37], "class1": [36, 37], "class_nam": [3, 9], "class_to_index": [36, 37], "class_val": 9, "class_valu": 9, "classic": [7, 9, 13, 26, 37], "classif": [0, 3, 5, 6, 7, 8, 11, 12, 21, 23, 25, 30, 31, 32, 35], "classifi": [0, 1, 4, 7, 9, 10, 11, 26, 31, 37, 39], "classificaton": [1, 39], "classifii": 10, "claus": [], "clean": [1, 39], "clear": [1, 5, 10, 12, 13, 34, 39], "clearli": [0, 3, 5, 6, 7, 8, 28, 32, 33, 35, 36, 37], "clever": [1, 10, 39], "clf": [0, 6, 8, 9, 10, 31, 32], "clf3": 0, "clf_lasso": 6, "clf_ridg": 6, "cli": 15, "click": [], "clip": [3, 28, 34, 36, 37], "clock": 34, "clone": [15, 29], "close": [0, 1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 18, 28, 30, 31, 33, 34, 35, 37, 38, 39], "closer": [3, 5, 13, 32, 33, 34], "closest": [8, 11, 13, 14], "closur": [23, 31], "cloud": [23, 31], "cluster": [0, 1, 4, 6, 11, 23, 31, 35, 36, 37, 39], "cluster_label": 14, "cm": [1, 2, 3, 6, 8, 13, 33, 34, 39], "cmap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 31, 39], "cmap_arg": 6, "cmd": [9, 15], "cn_": 28, "cnn": [12, 37, 38], "cnn_kera": 3, "cntk": [23, 31], "co": [0, 2, 3, 6, 9, 13, 31, 35, 36], "code": [0, 3, 4, 6, 7, 8, 18, 19, 21, 22, 23, 24, 28, 30], "codebas": 39, "codec": [], "coef": [0, 31], "coef0": 8, "coef_": [0, 5, 6, 8, 9, 13, 16, 31, 32, 33, 34], "coeff": 5, "coeffici": [0, 3, 5, 6, 7, 8, 9, 13, 18, 24, 31, 32, 34, 35, 36, 37], "coerc": [0, 6, 31, 35, 36], "coin": [10, 28], "coin_toss": 10, "col": [0, 11, 31, 32], "colab": [21, 22, 23, 31], "cold": 9, "colinear": [], "collabor": [20, 25, 26], "collaps": 8, "collect": [2, 6, 10, 11, 17, 23, 28, 30, 31, 35, 36, 38], "collinear": [5, 32, 33], "color": [0, 3, 4, 6, 8, 9, 10, 28, 34], "color_channel": 3, "color_cod": 6, "colorbar": [1, 6, 20], "coloumn": 39, "colsample_bytre": 10, "colsaobject": 10, "column": [0, 1, 2, 5, 6, 7, 8, 9, 11, 12, 16, 17, 18, 19, 24, 31, 32, 33, 34, 35, 36, 37, 38, 39], "columntransform": 9, "com": [4, 6, 15, 16, 19, 20, 21, 22, 23, 25, 26, 30, 31, 33, 34, 35, 36, 37, 38, 39], "combin": [1, 2, 5, 6, 7, 10, 15, 18, 22, 28, 35, 36, 39], "come": [0, 1, 3, 4, 5, 12, 13, 14, 15, 26, 31, 32, 33, 34, 37, 38, 39], "comfort": [], "command": [0, 1, 15, 39], "comment": [0, 4, 5, 6, 20, 25, 26], "commerci": [0, 23, 25, 31], "commit": 15, "commod": [0, 31], "common": [0, 1, 3, 5, 6, 7, 9, 11, 13, 14, 16, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "commonli": [0, 1, 4, 6, 7, 9, 13, 14, 32, 34, 35, 36, 37, 39], "commonmark": [], "commun": [0, 12, 15, 25, 37, 38], "commut": 3, "commutatitav": 3, "compact": [0, 1, 3, 5, 6, 7, 9, 11, 12, 13, 14, 21, 31, 32, 35], "compair": 0, "compar": [0, 3, 4, 5, 6, 11, 13, 18, 24, 25, 26, 31, 32, 33, 34, 35, 36, 38], "comparison": [2, 4, 13, 26], "compat": [7, 36, 37], "compens": 34, "compet": 0, "competit": 10, "compil": [0, 1, 3, 4, 13, 23, 24, 31, 39], "compl": 21, "complet": [0, 2, 3, 4, 9, 12, 15, 16, 17, 18, 19, 20, 21, 22, 31, 37], "completenn": [12, 37], "complex": [1, 5, 8, 9, 11, 12, 13, 16, 19, 31, 33, 34, 35, 36, 39], "complianc": [], "complic": [0, 1, 9, 13, 25, 26, 31, 33, 34, 35, 36, 39], "compoment": 32, "compon": [0, 1, 3, 4, 5, 6, 7, 9, 14, 16, 23, 31, 32, 33, 35, 37, 38, 39], "components_": 11, "compos": [9, 12, 13, 14, 23, 31, 37, 38], "compphys": [0, 6, 16, 20, 23, 25, 26, 27, 29, 30, 31, 32, 33, 36, 37, 39], "compress": [0, 31, 32], "compris": 6, "compromis": [5, 32, 33], "compulsori": [23, 31], "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, 30, 31, 32, 33, 35, 36, 37, 38, 39], "computation": [0, 3, 6, 9, 13, 28, 31, 33, 34, 38], "computationalscienceuio": 31, "compute_gradi": 22, "computerlab": [25, 26], "con": 26, "concaten": [2, 4, 6, 14, 36, 37], "concav": [1, 13, 32, 33], "concentr": 10, "concept": [0, 2, 23, 31, 32], "conceptu": [12, 13, 33, 37, 38], "concern": [0, 1, 4, 7, 31, 33, 36, 37, 39], "concic": 31, "conclud": [0, 5, 13, 34], "conclus": [1, 39], "cond": 2, "conda": [0, 1, 23, 25, 31, 39], "condis": 32, "condit": [0, 2, 4, 5, 6, 8, 9, 11, 13, 28, 31, 32, 34, 35], "conduct": 23, "condwav": 2, "confid": [0, 5, 6, 7, 8, 19, 31, 32, 36, 37], "configur": 3, "confirm": [5, 12, 21, 37], "conform": [], "confus": [5, 6, 7, 10, 24, 32, 35], "confusion_matrix": 9, "congruenti": 28, "conjug": [4, 8], "conjugaci": 13, "conjunct": 3, "connect": [0, 1, 3, 4, 9, 11, 12, 13, 24, 31, 32, 33, 37, 38, 39], "consensu": 34, "consequ": [5, 6, 8, 10, 12, 13, 32, 33, 34, 35], "consequenti": [], "conserv": [5, 14, 32, 33], "consid": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 16, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "consider": [0, 1, 5, 13, 31, 32, 33, 35], "consist": [1, 2, 3, 4, 6, 12, 13, 25, 26, 28, 32, 33, 35, 36, 37, 38, 39], "consol": [], "const": [], "constant": [0, 2, 4, 5, 6, 8, 12, 13, 16, 18, 28, 31, 32, 33, 34, 37, 38, 39], "constitu": [0, 31], "constitut": [2, 6, 35, 36], "constrain": [1, 3, 5, 7, 11, 33, 36, 39], "constraint": [5, 6, 8, 13, 32, 33, 35], "construct": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 24, 28, 31, 32, 35, 37], "constructor": [], "consult": 26, "consum": 34, "contact": [0, 31], "contain": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 18, 19, 21, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "contemporari": 31, "content": [1, 15, 20, 23, 24, 31, 33, 34], "context": [6, 10, 13, 22, 25, 33, 34, 35, 36, 38], "contigu": 24, "contin": 19, "continu": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 38, 39], "contour": [9, 10, 13], "contourf": [8, 9, 10], "contract": [], "contrast": [1, 4, 9, 10, 12, 31, 34, 37, 38, 39], "contribut": [0, 3, 5, 13, 18, 28, 31, 32, 33, 34], "contributor": [0, 25], "control": [0, 1, 3, 9, 13, 15, 23, 31, 39], "conv": [3, 4], "conv2d": [3, 4], "conv2dtranspos": 4, "convei": 31, "conveni": [5, 6, 12, 13, 24, 25, 26, 31, 33, 34, 35, 37], "convent": [12, 32], "converg": [1, 2, 4, 5, 8, 13, 14, 18, 32, 33, 38, 39], "convergencewarn": [], "convers": [20, 34], "convert": [0, 1, 4, 5, 9, 11, 13, 24, 31, 32, 33, 36, 37], "converttomatrix": 4, "convex": [4, 5, 7, 32, 36, 37], "convinc": [13, 33], "convolut": [1, 4, 23, 31, 39], "cool": [4, 9], "coolwarm": 6, "coordin": [5, 12, 14, 32, 33, 34, 37], "coorel": [], "copi": [0, 1, 14, 15, 32, 36, 37, 39], "copyright": [], "core": 10, "corel": 31, "coronari": [7, 36], "corr": [5, 7, 11, 32, 37], "correalt": [11, 23], "correct": [0, 1, 2, 3, 4, 5, 7, 13, 15, 19, 20, 21, 22, 24, 28, 31, 32, 33, 35, 36, 37, 39], "correctli": [1, 2, 6, 7, 10, 18, 19, 21, 22, 25, 26, 35, 36, 39], "correl": [0, 1, 3, 5, 6, 7, 10, 12, 13, 23, 28, 31, 33, 34, 35, 38], "correlation_matrix": [5, 7, 11, 32, 37], "correspond": [0, 3, 5, 6, 8, 9, 11, 12, 23, 24, 25, 26, 28, 31, 32, 33, 35, 37, 38], "cortex": [12, 37, 38], "cosin": [3, 6, 35, 36], "cost": [0, 2, 3, 5, 6, 7, 8, 9, 12, 13, 16, 17, 18, 19, 21, 22, 25, 26, 31], "cost_autograd": 22, "cost_deep_grad": 2, "cost_der": 22, "cost_fun": 22, "cost_func": 39, "cost_func_deriv": 39, "cost_funct": 2, "cost_function_deep": 2, "cost_function_deep_grad": 2, "cost_function_grad": 2, "cost_function_train": 39, "cost_function_v": 39, "cost_grad": [2, 22], "cost_histori": [], "cost_ol": [], "cost_one_lay": 22, "cost_ridg": [], "cost_sum": 2, "cost_two_lay": 22, "costcrossentropi": 39, "costli": 34, "costlogreg": 39, "costol": [13, 34, 39], "could": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 17, 18, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "coulomb": [0, 31], "count": [0, 9, 15, 25, 26, 27, 28, 29, 31], "counter": [25, 26], "counteract": 34, "counterpart": 31, "countor": 13, "coupl": [4, 5, 6, 21, 35], "cours": [0, 1, 3, 5, 11, 15, 16, 17, 19, 20, 21, 25, 26, 29, 32, 35, 36, 39], "coursework": 15, "courvil": [26, 30, 31, 32, 34], "cov": [5, 6, 11, 24, 28, 31, 32, 35], "cov_xi": [5, 11, 32], "cov_xx": [5, 11, 32], "cov_yi": [5, 11, 32], "covari": [0, 7, 23, 24, 31, 33, 37], "covariance_matrix": [5, 11, 14], "cover": [0, 5, 23, 25, 26, 29, 30, 32, 33, 35], "covert": [0, 31], "covxi": 28, "covxx": 28, "covxz": 28, "covyi": 28, "covyz": 28, "covzz": 28, "cpu": [1, 39], "cqofi41lfdw": [38, 39], "craft": 3, "crash": 34, "creat": [1, 3, 4, 5, 9, 10, 11, 12, 15, 18, 19, 21, 22, 23, 31, 34, 36, 37, 38, 39], "create_biases_and_weight": [1, 39], "create_convolutional_neural_network_kera": 3, "create_lay": [21, 22], "create_layers_batch": 21, "create_neural_network_kera": [1, 39], "create_x": [5, 11, 39], "creation": [], "credit": [0, 7, 29, 31, 36, 37], "crim": [], "crime": [], "criteria": [0, 4, 9, 10, 14, 28, 31], "criterion": [9, 10, 13, 18, 33, 34, 38], "critic": [6, 25, 32], "critiqu": [25, 26], "cross": [0, 1, 3, 7, 9, 10, 13, 15, 21, 22, 23, 26, 28, 31, 32, 33, 34, 39], "cross_entropi": [4, 21], "cross_val_scor": [6, 35, 36], "cross_valid": [7, 10, 37], "crossvalid": [6, 35, 36], "crucial": [1, 28, 34, 39], "cs231": 3, "csr_matrix": [24, 31], "css": [], "csv": [0, 4, 6, 7, 9, 35, 36, 37], "ctnk": [1, 39], "cube": 38, "cubic": 0, "culprit": [], "cumbersom": [5, 35], "cumprod": [], "cumsum": [10, 11, 31], "cumul": [7, 10, 28, 34], "cumulative_heads_ratio": 10, "cup": 5, "current": [1, 2, 3, 4, 13, 14, 15, 16, 30, 33, 34, 36, 37, 39], "curs": [0, 32], "curv": [6, 7, 10, 12, 25, 36, 37, 39], "curvatur": [13, 33, 34], "custom": [6, 14], "custom_cmap": [9, 10], "custom_cmap2": [9, 10], "custom_lin": [], "cutpoint": 9, "cv": [6, 7, 10, 35, 36, 37], "cvxbook": [13, 33], "cvxopt": [5, 8, 32], "cybenko": 38, "cycl": [1, 12, 37, 38, 39], "cycler": [], "d": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 19, 20, 21, 22, 24, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "d1": [], "d166a3": [], "d2": [], "d2_g_t": 2, "d2a8ff": [], "d4d0ab": [], "d71835": [], "d9dee3": [], "d_f": [13, 33], "d_g_t": 2, "d_net_out": 2, "da": [3, 22, 38], "da_1": 22, "dagger": [5, 24, 32, 33], "dai": [1, 9, 23, 39], "damag": [], "damp": 3, "darget": 9, "darkr": 28, "dat": [0, 31], "dat_id": [0, 6, 7, 9, 31, 35, 36], "data": [2, 4, 5, 8, 10, 12, 13, 14, 16, 19, 20, 22, 24, 25, 26, 30, 33, 34, 35], "data1": 14, "data2": 14, "data3": 14, "data4": 14, "data_id": [0, 6, 7, 9, 31, 35, 36], "data_indic": [1, 39], "data_panda": 31, "data_path": [0, 6, 7, 9, 31, 35, 36], "databas": [1, 39], "datafil": [0, 6, 7, 9, 31, 35, 36], "datafram": [0, 4, 5, 7, 9, 11, 31, 32, 37], "datapoint": [1, 5, 6, 7, 11, 13, 16, 33, 34, 35, 36, 39], "datasci": [15, 16, 19], "dataset": [0, 4, 6, 7, 8, 9, 10, 11, 13, 14, 16, 21, 22, 25, 26, 31, 33, 34, 35, 36, 37], "datatyp": 4, "date": [15, 18, 21, 22, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "daughter": 10, "davi": [], "david": 30, "davison": [35, 36], "db": [22, 38], "db_1": 22, "dbb7ff": [], "dbh": [1, 39], "dbo": [1, 39], "dc": 22, "dc5e85cd93c3": 26, "dc_da": 22, "dc_da1": 22, "dc_da2": 22, "dc_db": 22, "dc_db1": 22, "dc_db2": 22, "dc_dw": 22, "dc_dw1": 22, "dc_dw2": 22, "dc_dz": 22, "dc_dz1": 22, "dc_dz2": 22, "dcc6e0": [], "dcomposit": 24, "ddot": 2, "de": 34, "dead": [1, 39], "deadlin": [15, 20, 21, 22], "deal": [0, 1, 3, 5, 6, 8, 11, 13, 14, 19, 24, 28, 31, 32, 33, 34, 38, 39], "dealt": 0, "debt": [7, 36, 37], "debug": [0, 5, 6, 32, 33, 34, 35, 36, 39], "debugg": [], "decad": [0, 3, 34], "decai": [0, 13, 28, 31], "decemb": [29, 31], "decent": 10, "decid": [0, 2, 3, 5, 6, 9, 18, 32, 33, 34, 35, 36, 39], "decim": [0, 31, 39], "decis": [0, 1, 8, 11, 23, 30, 31, 39], "decision_funct": 8, "decision_tre": 9, "decisiontreeclassifi": [9, 10], "decisiontreeregressor": [0, 9, 10], "declar": [0, 4, 20, 24, 31], "declare_namespac": [], "decompos": [5, 6, 24, 32, 33, 38], "decomposit": [0, 6, 12, 31, 37, 38], "decompost": [5, 32, 33], "deconvolut": 3, "decorrel": [10, 13, 34], "decreas": [1, 2, 4, 5, 6, 10, 11, 13, 19, 33, 34, 35, 36, 39], "dedic": 20, "deduc": [0, 31], "deep": [3, 7, 12, 13, 23, 26, 30, 32, 33], "deep_neural_network": 2, "deep_param": 2, "deep_tree_clf": [9, 10], "deep_tree_clf1": 9, "deep_tree_clf2": 9, "deepcopi": 39, "deepen": [5, 23, 31], "deeper": [0, 3, 4, 31], "deeplearningbook": [26, 30, 31, 33, 34], "deer": 3, "def": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 16, 17, 21, 22, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "def_covari": 28, "default": [0, 1, 2, 4, 6, 7, 24, 26, 31, 32, 36, 37, 39], "default_tim": 4, "defect": [5, 32, 33], "defici": [5, 32, 33], "defin": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 25, 28, 32, 33, 34, 35, 36, 37], "definit": [1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 24, 28, 32, 33, 34, 35, 36, 37], "defint": 28, "defualt": 39, "degre": [3, 5, 6, 8, 9, 10, 11, 15, 16, 19, 20, 25, 28, 31, 33, 34, 35, 36], "deisenroth": 32, "del": 1, "delet": [6, 15], "delimit": 4, "deliv": [15, 25, 26, 27, 31], "delta": [0, 2, 3, 6, 8, 12, 13, 14, 31, 34, 38, 39], "delta_": [1, 24, 38, 39], "delta_0": [3, 38], "delta_1": [3, 38, 39], "delta_2": [3, 38, 39], "delta_2a_1": [38, 39], "delta_3": 3, "delta_4": 3, "delta_5": 3, "delta_h": [0, 1, 31, 39], "delta_i": [38, 39], "delta_j": [3, 12, 38, 39], "delta_k": [12, 38, 39], "delta_l": [1, 3, 39], "delta_matrix": 39, "delta_momentum": [13, 34], "delta_n": [0, 3, 31], "delug": 23, "delv": 0, "demand": [13, 33], "demonstr": [0, 3, 5, 6, 7, 11, 12, 19, 23, 31, 32, 33, 34, 35, 36, 37, 39], "demystifi": [37, 38, 39], "den": 4, "denomin": [1, 5, 34, 39], "denot": [1, 2, 6, 7, 13, 28, 33, 34, 36, 37, 39], "dens": [1, 3, 4, 39], "densiti": [0, 2, 6, 28, 35, 36], "depart": [29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "depend": [0, 1, 2, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 23, 24, 25, 28, 31, 32, 33, 34, 36, 37, 38, 39], "depict": 28, "deploy": [0, 23, 25, 31], "depth": [0, 3, 9, 10, 24, 35, 39], "der": [], "deriv": [0, 1, 2, 6, 7, 8, 10, 11, 13, 18, 22, 23, 25, 26, 31, 36, 37], "derivati": 13, "derivative_fn": 13, "derivb1": [38, 39], "derivb2": [38, 39], "derivw1": [38, 39], "derivw2": [38, 39], "descend": [5, 9, 11, 32, 33], "descent": [0, 1, 3, 7, 8, 12, 22, 26, 31, 32, 36, 38, 39], "describ": [0, 2, 4, 5, 6, 8, 10, 11, 12, 13, 19, 20, 24, 25, 26, 31, 34, 35, 37, 38], "descript": [0, 8, 9, 20, 25, 26, 31, 39], "design": [0, 1, 3, 4, 5, 6, 7, 10, 11, 12, 13, 17, 18, 25, 26, 31, 33, 34, 35, 36, 37, 38, 39], "designmatrix": [0, 31], "desir": [0, 2, 4, 5, 13, 14, 31, 32, 33, 34, 39], "desktop": 15, "despit": [1, 12, 34, 37, 39], "destroi": 24, "det": [5, 24, 32, 33], "detail": [0, 6, 11, 13, 14, 18, 21, 22, 24, 25, 32, 33, 34, 39], "detect": [3, 8, 12, 37, 38], "determin": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 18, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "determinist": [7, 13, 28, 33, 34, 36, 38], "deternin": 38, "dev": [1, 25, 26, 39], "develop": [0, 3, 5, 8, 10, 11, 12, 23, 24, 25, 26, 31, 32, 37, 38], "deviat": [0, 1, 2, 4, 5, 6, 17, 18, 19, 25, 28, 31, 32, 34, 35, 36, 39], "devis": [12, 37, 38], "df": [4, 8, 11, 13, 31, 38], "df1": 31, "di": [], "diag": [5, 8, 32, 33, 34], "diagnost": [1, 10, 39], "diagon": [0, 5, 7, 13, 18, 19, 24, 28, 31, 32, 33, 34, 36, 37, 39], "diagonaliz": [5, 32, 33], "diagram": 10, "diagsvd": 6, "dice": [6, 28, 35], "dict": [6, 8, 39], "dictionari": 39, "did": [0, 1, 5, 6, 7, 10, 11, 14, 16, 22, 25, 26, 31, 35, 36, 37, 39], "die": [1, 39], "diff": [2, 38], "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, 24, 25, 28, 30, 31, 32, 33, 35, 36, 37, 38, 39], "different": [38, 39], "differenti": [0, 3, 16, 21, 22, 23, 24, 26, 31, 32, 33, 37, 39], "difficult": [0, 1, 6, 10, 13, 28, 31, 34, 35, 36, 39], "difficulti": [0, 1, 13, 31, 33, 34, 39], "diffonedim": 2, "digit": [0, 1, 3, 4, 6, 26, 29, 31, 39], "digress": 38, "dilemma": [13, 34], "dilut": [1, 39], "dim": [4, 11, 14, 24, 39], "dimens": [0, 1, 2, 3, 4, 5, 8, 11, 14, 16, 24, 31, 32, 33, 38, 39], "dimension": [0, 4, 5, 6, 9, 11, 13, 14, 19, 23, 24, 25, 26, 31, 32, 33, 34, 35], "dimensionless": [0, 3, 31], "diment": 24, "diminish": 34, "dimnsion": 4, "diod": 3, "direct": [0, 1, 2, 4, 11, 12, 13, 14, 31, 32, 33, 34, 37, 38, 39], "directli": [1, 4, 5, 6, 18, 22, 28, 32, 33, 39], "directori": [], "disadvantag": [0, 31, 34], "disappear": [3, 6, 35], "disc_loss": 4, "disc_tap": 4, "discard": [6, 11, 34, 35, 36], "disciplin": [0, 3, 12, 37, 38], "disclaim": 28, "discontinu": 38, "discord": [21, 31], "discourag": [13, 15, 33], "discov": [0, 31], "discover": 5, "discret": [1, 3, 5, 7, 13, 36, 37, 39], "discrimin": [4, 7, 10, 11, 36, 37], "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, 23, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 38, 39], "diseas": [7, 36, 37], "disguis": [6, 32, 34], "disk": 34, "disord": [1, 7, 36, 37], "dispai": [37, 38], "displai": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 25, 28, 31, 32, 34, 35, 36, 37, 38, 39], "displaystyl": [0, 5, 17, 31, 32, 33, 34], "disregard": [0, 31], "dissimilar": [11, 14], "dist": 14, "distanc": [8, 9, 11, 14, 28], "distance_list": 9, "distinct": [3, 7, 8, 9, 10, 14, 36, 37], "distinctli": 8, "distinguish": [0, 4, 7, 8, 28, 31, 37], "distplot": [], "distribut": [0, 1, 4, 6, 7, 10, 11, 13, 14, 18, 19, 21, 23, 24, 25, 26, 31, 32, 33, 34, 36, 39], "distrubut": [0, 23, 25, 31], "div": [], "dive": [0, 8, 24, 31], "diverg": [1, 13, 33, 34, 39], "divid": [0, 1, 3, 5, 6, 7, 8, 9, 11, 12, 18, 19, 26, 28, 31, 32, 34, 35, 36, 37, 38, 39], "divis": [6, 8, 9, 13, 18, 24, 28, 34, 35, 36, 38, 39], "dl": [], "dm": [], "dna": [7, 36, 37], "dnn": [0, 1, 2, 4, 12, 31, 37, 38, 39], "dnn1": 4, "dnn2_gru2": 4, "dnn_kera": [1, 39], "dnn_model": 1, "dnn_numpi": [1, 39], "dnn_scikit": [0, 1, 31, 39], "do": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 24, 25, 26, 31, 32, 33, 35, 36, 38], "doc": [0, 15, 16, 19, 23, 25, 26, 27, 29, 30, 31, 39], "document": [4, 13, 15], "docutil": [], "doe": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 17, 18, 19, 21, 22, 24, 25, 26, 28, 31, 34, 35, 36, 38, 39], "doesn": [3, 9, 12, 31, 34, 38, 39], "dog": [1, 3, 4, 39], "dollar": [], "domain": [5, 8, 13, 25, 26, 33, 35], "domcontentload": [], "domin": [0, 31], "don": [0, 1, 3, 5, 6, 8, 11, 13, 15, 16, 21, 23, 25, 26, 31, 32, 34, 39], "done": [0, 2, 3, 4, 5, 6, 9, 10, 11, 13, 16, 20, 22, 24, 25, 31, 32, 33, 34, 35, 36, 38, 39], "dot": [0, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 18, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "doubl": [3, 4, 16, 24, 31], "doubli": [1, 39], "doubt": [25, 26], "down": [0, 3, 6, 9, 11, 12, 13, 33, 34, 37], "download": [0, 1, 3, 5, 6, 15, 20, 24, 30, 31, 39], "downsampl": 3, "downscal": 26, "dozen": [1, 39], "dq": [6, 35], "draft": 20, "drag": 13, "dragon": [], "dramat": 11, "drastic": 4, "draw": [4, 6, 10, 13, 33, 35, 36], "drawback": [0, 1, 3, 13, 32, 33, 34, 39], "drawn": [1, 4, 6, 7, 11, 28, 31, 35, 36, 37, 39], "drive": [3, 4, 21, 22], "driven": 3, "drop": [0, 1, 5, 6, 11, 13, 28, 31, 32, 33, 35, 39], "dropna": [0, 6, 31, 35, 36], "dropout": 4, "dt": [2, 3, 13, 28, 38], "dtype": [0, 1, 3, 4, 14, 24, 31, 36, 37, 38, 39], "dual": [], "dub": [0, 31], "duboi": [], "due": [1, 2, 5, 6, 8, 10, 12, 13, 18, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "dugard": [], "dummi": [], "dure": [0, 1, 3, 4, 8, 9, 11, 20, 23, 25, 26, 31, 34, 35, 36, 37, 39], "dw": 22, "dw_1": 22, "dwell": [], "dwh": [1, 39], "dwo": [1, 39], "dx": [2, 3, 8, 28, 38], "dx_1": 28, "dx_1p": [6, 35], "dx_2p": [6, 35], "dx_mp": [6, 35], "dx_n": 28, "dxp": [6, 35], "dy": [1, 8, 28, 39], "dynam": 4, "dz": [8, 22], "dz_1": 22, "dz_2": 22, "e": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "e1e1e1": [], "e_": [0, 2, 31], "e_z": 21, "each": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 22, 23, 24, 26, 27, 28, 29, 31, 32, 33, 34, 35, 37, 38, 39], "eager": 35, "eapprox": [0, 31], "earli": [1, 13, 34, 39], "earlier": [0, 5, 7, 8, 9, 11, 12, 13, 19, 20, 21, 22, 31, 32, 36, 37, 38, 39], "earthexplor": 6, "eas": [6, 9, 14, 35], "easi": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 21, 22, 23, 24, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "easier": [5, 6, 8, 9, 13, 15, 20, 21, 22, 25, 26, 28, 31, 32, 33, 35, 36], "easiest": [13, 18, 36, 37], "easili": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 24, 25, 31, 32, 33, 34, 35, 36, 37, 38, 39], "eastern": [29, 31], "ebind": [0, 31], "eblock": 9, "ec8e2c": [], "econom": [], "econometr": 31, "economi": 5, "ecosystem": [23, 31], "ect": 27, "edg": 3, "edgecolor": [6, 35, 36], "edit": [21, 22], "editor": [15, 20], "edu": [13, 25, 26, 33], "educ": [0, 25, 26, 31, 35], "ee6677": [], "eff": 28, "effect": [1, 4, 10, 13, 16, 17, 18, 28, 34, 39], "effic": [1, 39], "effici": [0, 3, 10, 13, 21, 22, 23, 24, 28, 31, 34, 36, 37, 38], "effort": 19, "efron": [6, 35, 36], "egrad": 13, "eig": [5, 11, 13, 24, 28, 31, 32, 33, 34], "eigen": 28, "eigenpair": [5, 11, 32, 33], "eigenvalu": [0, 5, 8, 11, 13, 24, 31, 32, 33, 34], "eigenvector": [5, 11, 13, 32, 33], "eight": [24, 31], "eigval": [24, 28, 31], "eigvalu": [11, 13, 33, 34], "eigvec": [24, 28, 31], "eigvector": [11, 13, 33, 34], "eir": [29, 31], "eispack": [24, 31], "either": [1, 5, 6, 7, 8, 9, 10, 11, 13, 18, 19, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "eivind": 29, "eivinsto": 29, "ekstr\u00f8m": 4, "elabor": 28, "elarn": 3, "electr": [0, 3, 12, 31, 37, 38], "electron": 31, "eleg": 11, "element": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 19, 20, 21, 23, 24, 25, 26, 30, 32, 34, 35, 36, 37, 38, 39], "elementari": [10, 13, 24, 38], "elementwis": [3, 13], "elementwise_grad": [2, 13, 22, 39], "elessar": 31, "elif": [14, 39], "elim": 24, "elimin": [3, 8], "elin": [29, 31], "ell_": [], "ellipsi": 16, "els": [1, 3, 4, 7, 9, 12, 13, 16, 22, 24, 36, 37, 39], "elu": 1, "elus": [0, 31], "em": [], "email": [20, 21, 27, 29, 31], "emb": [], "embark": 38, "embed": [0, 11, 32], "embodi": [6, 25, 35, 36], "emit": 28, "emner": 30, "emph": 34, "emphas": [0, 10, 23, 31], "emphasi": [0, 23, 30, 31], "empir": [1, 11, 28, 39], "emploi": [0, 1, 5, 6, 11, 13, 26, 28, 31, 32, 33, 35, 39], "employ": 0, "empti": [6, 10, 15, 35, 36, 39], "emul": [12, 37, 38], "en": [23, 25, 30], "enabl": [11, 34, 39], "enbodi": [6, 35], "encod": [0, 3, 5, 9, 11, 14, 31, 32, 33, 36, 37], "encompass": [0, 25, 28], "encount": [0, 1, 5, 7, 13, 15, 21, 25, 28, 31, 32, 33, 34, 36, 37, 39], "encourag": [15, 25, 26], "end": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 20, 22, 24, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "endblock": [], "endfor": [], "endif": [], "endors": [], "endpoint": [3, 6], "energi": [0, 4, 6, 35, 36], "enforc": [12, 37, 38], "eng": 30, "engin": [0, 1, 3, 4, 23, 31, 39], "english": [25, 26], "enjoi": 34, "enocurag": [25, 26], "enorm": 3, "enough": [0, 6, 13, 26, 31, 33, 34, 35], "ensembl": [1, 9, 31, 39], "ensur": [0, 1, 2, 3, 5, 6, 11, 13, 18, 28, 32, 33, 34, 35, 36, 38, 39], "entail": 31, "enter": [5, 6, 32, 33, 34], "enthought": [0, 23, 25, 31], "entir": [1, 3, 7, 9, 21, 23, 28, 31, 34, 36, 39], "entireti": [], "entiti": [9, 12, 24, 31], "entri": [0, 5, 8, 11, 12, 24, 31, 32, 34, 35], "entropi": [1, 3, 7, 10, 13, 21, 22, 26, 31, 33, 34, 39], "enumer": [0, 1, 2, 3, 4, 6, 8, 21, 31, 32, 34, 36, 37, 39], "env": 28, "environ": [2, 21, 22, 23, 25, 31], "environemnt": 15, "eo": [0, 6, 35, 36], "eol": 0, "eosfit": 0, "epoch": [0, 1, 3, 4, 12, 13, 21, 31, 34, 36, 37, 39], "eppstein": [], "epsilon": [0, 5, 6, 7, 13, 25, 31, 32, 33, 34, 35, 36, 37, 38], "epsilon_": [0, 31], "epsilon_0": [0, 31], "epsilon_1": [0, 31], "epsilon_2": [0, 31], "epsilon_i": [0, 31, 32], "eq": [3, 13, 14, 24, 28, 33], "eqnarrai": [3, 5, 6, 35], "equal": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 16, 18, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 38, 39], "equat": [1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 17, 19, 24, 28, 31, 34, 35], "equilibrium": [2, 12, 37, 38], "equiv": [3, 13, 24, 28, 33, 34], "equival": [0, 1, 5, 7, 8, 11, 13, 23, 24, 26, 31, 32, 33, 34, 35, 39], "equivel": [19, 21, 22], "eras": [], "erf": 28, "eriador": 31, "eric": 39, "err": [0, 10], "err_": [6, 35, 36], "err_sqr": 2, "errat": [13, 33, 34], "erron": 2, "error": [1, 2, 4, 5, 6, 7, 9, 11, 12, 13, 15, 16, 17, 18, 19, 21, 23, 24, 25, 26, 28, 34, 37, 38, 39], "error_estimate_corr_tim": 28, "error_hidden": [1, 39], "error_output": [1, 39], "escap": [13, 33, 34], "escapehtml": [], "especi": [1, 3, 9, 12, 13, 15, 18, 25, 26, 34, 37, 38, 39], "essenti": [0, 5, 6, 9, 10, 12, 14, 15, 25, 26, 28, 32, 33, 34, 37, 38, 39], "establish": [0, 6, 10, 11, 16, 25, 26], "estim": [0, 1, 5, 6, 7, 10, 11, 13, 23, 28, 31, 32, 33, 34, 36, 37, 39], "estimated_mse_fold": [6, 35, 36], "estimated_mse_kfold": [6, 35, 36], "estimated_mse_sklearn": [6, 35, 36], "et": [0, 2, 4, 16, 17, 20, 26, 30, 31, 32, 33, 35, 36, 37, 38, 39], "eta": [0, 1, 3, 8, 12, 13, 18, 26, 31, 33, 34, 38, 39], "eta0": [8, 13], "eta_": 13, "eta_j": 34, "eta_t": [13, 34], "eta_v": [0, 1, 3, 31, 39], "etc": [0, 1, 3, 5, 7, 8, 9, 11, 12, 13, 14, 23, 24, 25, 26, 28, 32, 33, 34, 36, 37, 39], "ethic": 23, "etsim": 35, "euclidean": [0, 14, 32, 34], "euler": [], "evalu": [0, 2, 3, 4, 5, 6, 9, 13, 15, 16, 17, 19, 21, 25, 28, 31, 32, 33, 34, 35, 36, 37], "evalut": [13, 25], "even": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 22, 23, 24, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "evenli": 4, "event": [5, 7, 10, 28, 35, 36], "eventu": [0, 5, 6, 11, 12, 13, 25, 26, 29, 32, 33, 34, 35, 36, 37, 38], "everi": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 12, 13, 14, 15, 21, 23, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "everyth": [4, 12, 16, 18, 21, 38, 39], "everywher": [4, 13, 33], "evolv": 0, "exact": [0, 5, 11, 12, 13, 24, 28, 31, 32, 34, 38, 39], "exactli": [0, 3, 4, 6, 12, 18, 23, 32, 34, 35, 37, 38, 39], "exam": 31, "examin": [6, 35, 36], "exampl": [0, 5, 11, 12, 13, 15, 16, 18, 20, 23, 24, 25, 26, 28, 30], "exce": [1, 12, 13, 34, 37, 38, 39], "exceed": 34, "excel": [0, 1, 4, 5, 10, 20, 25, 26, 31, 32, 39], "except": [3, 4, 6, 8, 9, 24, 39], "excess": [0, 31], "exchang": 34, "excit": 0, "exclud": [1, 6, 12, 25, 26, 32, 34, 35, 36, 37, 39], "exclus": [0, 1, 3, 6, 28, 31, 35, 36, 39], "execut": [2, 5, 13, 15, 32, 33, 34], "exemplari": [], "exemplifi": [13, 34], "exercic": [29, 31], "exercis": [5, 23, 25, 26, 27, 29, 31, 33, 34, 35, 36, 37, 39], "exercisesweek41": 26, "exercisesweek42": [26, 39], "exhaust": [6, 34, 35, 36], "exhibit": [0, 5, 6, 8, 31, 32, 35], "exist": [0, 1, 2, 3, 5, 6, 7, 8, 9, 13, 19, 24, 25, 26, 31, 33, 34, 35, 36, 39], "exit": [5, 24, 32, 33], "exp": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 16, 17, 19, 21, 22, 28, 32, 33, 34, 35, 36, 37, 38, 39], "exp_term": [1, 39], "exp_z": [36, 37], "expand": [5, 7, 11, 13, 33, 36, 37], "expans": [0, 3, 5, 8, 10, 12, 13, 31, 32, 33, 38], "expect": [0, 1, 5, 6, 7, 11, 12, 13, 15, 18, 23, 25, 26, 31, 32, 34, 36, 38, 39], "expectation_value_of_h_wrt_p": 28, "expens": [6, 10, 13, 16, 33, 34], "experi": [0, 1, 6, 8, 13, 15, 23, 25, 31, 32, 33, 34, 35, 36, 39], "experiment": [0, 4, 6, 9, 28, 31, 35, 36], "expert": [1, 9, 39], "explain": [0, 6, 9, 10, 11, 13, 16, 19, 25, 26, 31, 33, 36, 37], "explained_variance_ratio_": 11, "explan": [], "explanatori": [0, 31], "explicit": [0, 3, 6, 13, 24, 25, 31, 32, 33, 34], "explicitli": [0, 4, 21], "explod": [1, 38], "exploit": [0, 3, 12, 13, 31, 34, 37, 38], "explor": [1, 4, 6, 8, 13, 18, 23, 25, 26, 31, 33, 34, 39], "expon": [1, 39], "exponenti": [0, 1, 5, 6, 10, 13, 28, 31, 33, 38, 39], "export": [9, 15, 16, 19, 20, 36, 37], "export_graphviz": 9, "export_text": 9, "exporttext": 9, "expos": 23, "expr": 38, "express": [0, 2, 3, 5, 6, 7, 10, 12, 13, 18, 22, 24, 25, 26, 28, 31, 33, 34, 35], "exptmean": 28, "exptvari": 28, "extend": [0, 2, 7, 11, 13, 23, 31, 34], "extend_path": [], "extens": [0, 12, 15, 23, 26, 31, 37, 38], "extent": [0, 1, 6, 30, 35, 36, 39], "extern": [3, 6, 9], "extra": [1, 3, 5, 15, 29, 31, 32, 33, 39], "extract": [0, 3, 5, 6, 7, 8, 11, 13, 16, 17, 24, 26, 31, 32, 36, 37, 38], "extrapol": [0, 31], "extrem": [0, 1, 4, 5, 6, 7, 8, 9, 13, 15, 16, 24, 32, 33, 34, 36, 39], "extremum": [13, 33], "extrins": 11, "ey": [0, 5, 6, 13, 14, 18, 24, 31, 32, 33, 34], "f": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 13, 14, 15, 16, 17, 18, 19, 22, 24, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "f1": 13, "f11": [0, 31], "f12": [0, 31], "f13": [0, 31], "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, 31], "f9_altern": 13, "f9_alternative_grad": 13, "f9_grad": 13, "f_": 10, "f_0": [3, 10], "f_1": [10, 13, 33], "f_2": [12, 13, 33, 37], "f_3": [12, 37], "f_d": 28, "f_grad": 13, "f_grad_analyt": 13, "f_i": [0, 6, 12, 16, 35, 36, 37], "f_m": [3, 10], "f_n": 3, "f_vec": 2, "face": [13, 31, 33], "facecolor": [6, 8, 28, 35], "facil": [0, 23], "facilit": [12, 37, 38], "fact": [0, 1, 3, 5, 9, 11, 12, 13, 22, 31, 32, 33, 34, 39], "facto": 34, "factor": [0, 1, 3, 5, 6, 9, 10, 11, 13, 24, 28, 31, 32, 33, 39], "factori": 13, "fad000": [], "fade": 6, "fae4c2": [], "fafab0": [9, 10], "fail": [0, 6, 13, 29, 31, 33, 35, 36, 38], "failur": [7, 36, 37], "fairli": [1, 2, 18, 28, 34, 39], "faisal": [16, 32], "fake": 4, "fake_loss": 4, "fake_output": 4, "fall": [8, 9, 27], "fals": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 14, 16, 17, 24, 26, 31, 32, 33, 34, 35, 36, 37, 39], "famili": [0, 7, 8, 28, 32, 34, 36, 37, 38], "familiar": [0, 3, 5, 6, 8, 15, 23, 24, 25, 28, 31, 35, 38], "famou": [6, 12, 39], "far": [0, 3, 4, 5, 6, 8, 11, 12, 13, 14, 16, 20, 21, 22, 31, 32, 33, 34, 37, 38], "fashion": [0, 9, 10, 26, 31, 34], "fashionmnist": 26, "fast": [1, 3, 6, 10, 12, 13, 23, 28, 31, 33, 34, 35, 36, 38, 39], "faster": [1, 11, 13, 21, 34, 39], "fastest": [13, 24, 33], "fatal": [], "favor": [7, 34, 36], "favorit": 28, "fc": 3, "fcfcfc": [], "fdac54": [], "fdf2e2": [], "featur": [0, 1, 3, 5, 6, 7, 8, 10, 11, 12, 13, 15, 17, 18, 19, 21, 23, 26, 28, 31, 33, 34, 35, 36, 37, 38, 39], "feature_nam": [1, 7, 9, 21, 37], "feautur": 9, "fed": [1, 38, 39], "feed": [0, 2, 3, 11, 21, 23, 26, 31], "feed_forward": [1, 21, 22, 39], "feed_forward_all_relu": 21, "feed_forward_batch": 21, "feed_forward_one_lay": 22, "feed_forward_out": [1, 39], "feed_forward_sav": 22, "feed_forward_train": [1, 39], "feed_forward_two_lay": 22, "feedback": [4, 20, 31], "feeddorward": 4, "feedforward": [1, 4, 12, 39], "feel": [0, 5, 6, 11, 13, 15, 16, 18, 21, 22, 23, 25, 26, 29, 31, 38], "feet": [], "fefef": [], "fefeff": [], "felt": [25, 26], "fenc": [], "fernando": [], "fetch": [6, 15, 26], "fetch_openml": 26, "few": [1, 3, 4, 5, 9, 17, 18, 19, 22, 28, 31, 38, 39], "fewer": [0, 9, 11, 19, 31, 34], "ff7b72": [], "ff9492": [], "ffa07a": [], "ffa657": [], "ffb757": [], "ffd700": [], "ffd900": [], "ffd9002e": [], "ffffff": [], "ffnn": [1, 12, 26, 37, 38, 39], "fi": [], "field": [0, 3, 6, 12, 19, 23, 37, 38], "fieldmask": [], "fifteen": 38, "fifth": [0, 6, 31], "fig": [0, 1, 2, 3, 4, 6, 7, 12, 13, 14, 25, 31, 36, 37, 39], "fig_id": [0, 6, 7, 9, 31, 35, 36], "figaxi": 28, "figsiz": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 31, 35, 36, 37, 39], "figur": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 23, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "figure_id": [0, 6, 7, 9, 31, 35, 36], "figurefil": [0, 6, 7, 9, 31, 35, 36], "file": [0, 4, 5, 6, 7, 9, 15, 20, 21, 22, 25, 26, 31, 35, 36], "file_prefix": 4, "filenam": 31, "fill": [5, 9, 18, 32, 33, 39], "fill_valu": [], "filter": [3, 4], "final": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 20, 21, 22, 25, 26, 27, 28, 29, 31, 33, 35, 36, 37], "financ": 0, "find": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 21, 22, 23, 25, 26, 28, 31, 32, 33, 34, 36, 37, 38, 39], "fine": [0, 14], "finish": [2, 20, 21, 39], "finit": [3, 5, 6, 12, 13, 17, 28, 32, 33, 35, 36, 37, 38], "finnicki": 15, "fire": [], "first": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 19, 21, 22, 24, 25, 26, 28, 29, 30, 32, 34, 35, 36, 37], "first_moment": 34, "first_term": 34, "firsteigvector": 11, "fit": [1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 17, 18, 19, 22, 25, 26, 28, 32, 34, 35, 36, 37, 38, 39], "fit_beta": 32, "fit_intercept": [0, 5, 6, 16, 32, 33, 34, 35, 36, 37], "fit_mod": 9, "fit_theta": [6, 34], "fit_transform": [0, 6, 8, 9, 11, 15, 19, 35, 36], "fiti": [0, 31], "five": [0, 9, 31, 32, 38], "fix": [0, 3, 4, 6, 10, 11, 12, 13, 25, 31, 35, 36, 37, 39], "flag": 4, "flat": [12, 13, 33, 34], "flatten": [1, 3, 4, 5, 24, 39], "flavor": [], "flexibl": [1, 6, 8, 10, 12, 26, 31, 34, 35, 36, 37, 39], "flip": [21, 29, 31], "float": [0, 3, 4, 5, 9, 11, 13, 14, 24, 31, 32, 33, 39], "float32": [4, 9, 39], "float64": [4, 24, 31, 37, 38, 39], "floatingpointerror": 39, "floor": 39, "flop": [5, 24, 32, 33], "flow": [1, 4, 12, 37, 38, 39], "flower": 21, "fluctuat": [5, 34], "flush": 39, "fly": 11, "fm": 0, "fmax": 3, "fmesh": 13, "fn": 7, "focu": [0, 3, 4, 5, 6, 15, 23, 25, 26, 30, 31, 32, 33, 34, 35, 36], "focus": [1, 6, 7, 24, 32, 34, 36, 37, 39], "fold": [6, 9, 25], "folder": [0, 4, 6, 15, 20, 25, 26, 31], "follow": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "font": [7, 20, 28, 31, 36], "fontdict": 28, "fontsiz": [1, 6, 8, 9, 10, 28], "fontweight": 1, "footprint": [3, 34], "foral": [8, 32, 38], "forc": [0, 5, 6, 10, 11, 32, 33, 34, 38], "forcast": 4, "forcier": [], "forecast": [4, 12, 37, 38], "forest": [0, 1, 9, 23, 31, 39], "forget": [11, 34], "form": [0, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "formal": [3, 4, 14, 18, 28, 38], "format": [0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 20, 23, 28, 30, 35, 36, 37, 39], "format_data": 4, "formatstrformatt": [6, 13, 33, 34], "formatt": [], "formul": [4, 6, 11, 14], "formula": [3, 13, 28, 33, 38], "forth": [4, 12, 22, 37], "fortran": [0, 23, 24, 31], "fortran2003": [23, 31], "fortran2008": [25, 26], "fortran90": 28, "fortun": [0, 11, 32], "forward": [0, 3, 6, 21, 23, 24, 26, 31, 34, 35], "forwardpropag": [38, 39], "found": [1, 2, 4, 5, 6, 12, 13, 19, 20, 21, 22, 25, 31, 32, 34, 35, 36, 37, 38, 39], "foundat": [23, 31], "four": [4, 5, 6, 8, 12, 21, 24, 27, 29, 31, 33, 37, 38, 39], "fourier": [0, 31, 38], "fourierdef1": 3, "fourierdef2": 3, "fourierseriessign": 3, "fourth": [12, 31, 32], "fp": 7, "frac": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "fraction": [9, 36, 37], "frame": [7, 34, 37], "framework": [1, 8, 10, 28, 39], "frank": [5, 11], "frankefunct": [5, 6, 11], "fredli": [21, 29, 31], "free": [0, 6, 11, 13, 15, 16, 18, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 38], "freecodecamp": 23, "freedom": [5, 33], "freeli": [0, 25], "freez": 15, "frequenc": [3, 6, 7, 28, 35, 37], "frequent": [0, 8, 9, 13, 33], "frequentist": 23, "fresh": 10, "fridai": [15, 21, 22, 29, 31], "friedman": [6, 19, 25, 30, 31], "friendli": 4, "fro": 25, "frodo": 31, "frog": 3, "from": [0, 1, 2, 3, 4, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 28, 29, 30], "from_cod": 9, "from_logit": [3, 4], "from_tensor_slic": 4, "front": [0, 4, 5, 31, 32, 33], "frustrat": 15, "fulfil": [2, 5, 12, 32, 33, 37, 39], "full": [1, 3, 5, 7, 9, 10, 13, 21, 26, 28, 31, 32, 33, 36], "full_matric": [5, 32, 33], "fulli": [3, 6, 12, 28, 35, 36, 37, 38], "fullnam": [], "fun": [23, 31], "func": [2, 21, 39], "function": [2, 3, 4, 5, 9, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], "functionali": 11, "fundament": [0, 6, 23, 31, 35, 36], "funtion": 2, "furnish": [], "furthemor": 38, "further": [2, 7, 9, 19, 31, 38], "furthermor": [0, 3, 5, 6, 7, 11, 12, 13, 23, 25, 26, 31, 32, 33, 34, 35, 36, 37, 39], "furthest": 22, "futur": [0, 4, 8, 9, 31], "fy": [15, 21, 25, 26, 27, 29, 30, 31], "fys4155": [25, 26], "fys5419": [30, 31], "fys5429": [30, 31], "f\u00f8470": [29, 31], "g": [0, 1, 2, 3, 4, 6, 8, 9, 10, 11, 13, 15, 18, 19, 28, 31, 32, 33, 34, 35, 36, 37, 39], "g0": 2, "g_": [2, 9, 10, 34], "g_0": 2, "g_1": [2, 10], "g_2": [2, 10], "g_3": 38, "g_analyt": 2, "g_dnn_ag": 2, "g_euler": 2, "g_i": [2, 38], "g_j": 38, "g_m": [3, 10], "g_n": 3, "g_re": 2, "g_t": [2, 34, 39], "g_t_d2t": 2, "g_t_d2x": 2, "g_t_dt": 2, "g_t_hessian": 2, "g_t_hessian_func": 2, "g_t_invers": 39, "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, 32, 33, 39], "galleri": [0, 31], "game": 4, "gamge": 31, "gamma": [0, 2, 8, 9, 10, 11, 13, 31, 33], "gamma1": 8, "gamma2": 8, "gamma_": [0, 31], "gamma_0": 10, "gamma_1": 10, "gamma_1x": 10, "gamma_i": [0, 8, 28, 31], "gamma_j": 13, "gamma_k": [13, 33], "gamma_m": 10, "gamma_x": [0, 31], "gap": [8, 34], "gate": [4, 12, 38], "gather": [0, 1, 12, 32, 37, 38, 39], "gaug": [12, 37, 38], "gaussbacksub": 24, "gaussian": [4, 5, 6, 8, 14, 18, 28, 31, 35, 36, 37], "gaussian_point": 14, "gaussian_rbf": 8, "gave": [13, 26, 34], "gavra": 31, "gbc": 31, "gca": [2, 6, 8, 13], "gd": [1, 33, 38, 39], "gd_clf": 10, "gdclassiffiercgain": 10, "gdclassiffierconfus": 10, "gdclassiffierroc": 10, "gdm": 13, "gdregress": 10, "ge": [1, 5, 7, 28, 32, 33, 36, 39], "gen_loss": 4, "gen_tap": 4, "gender": [0, 31], "genener": 4, "gener": [0, 1, 2, 3, 5, 6, 8, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, 24, 25, 26, 28, 30, 32, 33, 34, 35, 39], "generaliz": [16, 39], "generallay": [12, 37], "generate_and_save_imag": 4, "generate_binary_data": [36, 37], "generate_imag": 4, "generate_latent_point": 4, "generate_multiclass_data": [36, 37], "generate_simple_clustering_dataset": 14, "generated_imag": 4, "generator_loss": 4, "generator_loss_list": 4, "generator_model": 4, "generator_optim": 4, "genom": 23, "geodes": 11, "geoff": 34, "geometr": [0, 13, 31, 34], "geometri": 5, "georg": 30, "geotif": 6, "geq": [2, 5, 8, 9, 13, 32, 33, 34], "gerard": [], "geron": [0, 30, 31], "get": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 15, 19, 21, 22, 23, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 39], "get_dummi": 9, "get_paramet": 2, "get_split": 9, "get_yaxi": 8, "get_yticklabel": 6, "getmask": [], "gh": 15, "giant": 34, "gibb": [23, 31], "gif": 4, "gini": 10, "gini_index": 9, "ginvers": 13, "git": [0, 15, 23, 31], "gitcdn": [], "giter": [13, 34], "github": [0, 20, 23, 25, 26, 27, 29, 30, 31, 32, 38, 39], "gitignor": 15, "gitlab": [0, 15, 23, 25, 26, 31], "gitta": [38, 39], "give": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 18, 19, 23, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "given": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 21, 24, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "glkfgrjhtlnplbx4": 21, "global": [6, 7, 13, 33, 34, 36, 37], "gloriou": 26, "glorot": 1, "gmail": [], "gnew": 13, "go": [0, 1, 3, 5, 6, 8, 9, 11, 12, 13, 15, 16, 18, 21, 31, 32, 33, 35, 38, 39], "goal": [0, 7, 9, 31, 36, 37], "goe": [0, 1, 2, 5, 6, 13, 14, 15, 19, 24, 31, 32, 33, 34, 35, 39], "goessner": [], "golden": 13, "gone": [5, 32, 33], "gong": [1, 39], "good": [1, 3, 4, 5, 6, 9, 10, 11, 13, 15, 18, 21, 23, 28, 30, 32, 33, 34, 36, 38, 39], "goodfellow": [4, 26, 30, 31, 32, 33, 36, 37, 38, 39], "googl": [1, 4, 21, 22, 23, 31, 39], "got": [1, 6, 21, 22, 25, 26, 39], "gotten": [31, 39], "gov": 6, "govern": 31, "gp": 30, "gpu": [1, 13, 23, 31, 34, 39], "grad": [2, 13, 21, 22, 34, 39], "grad_analyt": 13, "grad_ol": 18, "grad_ridg": 18, "grad_two_lay": 22, "grade": [25, 26, 27], "gradient": [0, 3, 4, 7, 8, 9, 12, 21, 23, 31, 32, 36], "gradient_bia": 39, "gradient_desc": 34, "gradient_func": 21, "gradient_weight": 39, "gradientboostingclassifi": 10, "gradientboostingregressor": 10, "gradients_of_discrimin": 4, "gradients_of_gener": 4, "gradienttap": 4, "gradual": [1, 14, 39], "grai": [4, 6], "granger": [], "grant": [], "graph": [1, 9, 11, 12, 13, 16, 20, 33, 34, 37, 38, 39], "graph_from_dot_data": 9, "graphic": [0, 1, 9, 15, 31, 39], "grasp": 0, "gray_r": [1, 3, 39], "grayscal": 3, "great": [5, 13, 15, 21, 22, 33, 34, 38], "greater": [1, 7, 28, 32, 37, 39], "greatli": 13, "greedi": 9, "green": [0, 3, 9, 28], "gregor": 39, "grei": 4, "grid": [1, 3, 6, 7, 8, 12, 28, 32, 34, 35, 36, 37, 39], "groh": [38, 39], "grossli": [13, 33], "ground": [0, 31], "group": [0, 6, 7, 9, 14, 15, 20, 23, 25, 26, 27, 29, 31, 35], "groupbi": [0, 31], "grow": [1, 3, 9, 10, 34, 39], "growth": [0, 31], "gru": 4, "guarante": [0, 4, 13, 28, 31, 32, 33, 34], "guess": [1, 4, 10, 13, 14, 26, 33, 34, 39], "guestrin": 10, "gui": 15, "guid": [1, 21, 39], "guidelin": [20, 25, 26, 36, 37], "g\u00f6ssner": [], "h": [0, 1, 5, 6, 8, 13, 15, 19, 21, 28, 29, 30, 31, 32, 33, 34, 39], "h1": 2, "h_": [0, 13, 31, 33, 34], "h_0": 34, "h_1": [2, 13, 33], "h_2": [2, 13, 33], "h_m": 10, "h_t": 34, "ha": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "haanen": [29, 31], "habit": [0, 32], "had": [0, 1, 6, 7, 13, 31, 33, 34, 35, 36, 39], "hadamard": [1, 12, 13, 34, 38, 39], "half": [1, 8, 9, 36, 37, 38, 39], "halv": 10, "hand": [0, 1, 2, 3, 5, 11, 12, 13, 23, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 36, 37], "handi": [3, 25, 26], "handl": [0, 1, 2, 5, 9, 11, 15, 18, 22, 23, 32, 33, 34, 39], "handle_unknown": 9, "handsid": [12, 38, 39], "handwrit": [12, 37, 38], "handwritten": [1, 5, 39], "happen": [1, 2, 3, 4, 5, 6, 10, 13, 28, 32, 33, 34, 37, 39], "hard": [1, 7, 8, 10, 13, 21, 22, 33, 34, 36, 38, 39], "hardcopi": [23, 31], "harder": [0, 1, 19, 21, 32, 39], "harmon": 3, "hash": 34, "hasn": [], "hassl": [0, 23, 31], "hast": [23, 31], "hasti": [0, 6, 16, 17, 19, 20, 25, 30, 31, 32, 35, 36], "hat": [0, 1, 5, 6, 7, 9, 10, 11, 12, 13, 16, 17, 18, 19, 24, 32, 33, 34, 35, 37, 38], "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, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "have_sys_un_h": [], "haven": [1, 22, 39], "he": [7, 36, 37], "head": [4, 10, 28], "header": [0, 31], "heads_proba": 10, "health": [0, 32], "hear": [0, 13, 31, 34], "heart": [0, 7, 31, 36], "heatmap": [0, 1, 3, 7, 17, 20, 31, 37, 39], "heavi": 34, "heavili": 0, "heavisid": [1, 39], "height": [1, 3, 6, 32, 39], "held": [13, 34], "help": [0, 1, 4, 12, 13, 15, 16, 25, 26, 31, 34, 35, 37, 38, 39], "helper": [4, 14, 36, 37], "henc": [0, 5, 6, 8, 9, 10, 12, 13, 31, 32, 33, 34, 35, 36, 37], "henrik": [29, 31], "her": [7, 36, 37], "here": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "hereaft": [0, 8, 12, 31], "herebi": [], "hermitian": 24, "hessenberg": 24, "hessian": [0, 2, 5, 13, 36, 37], "heterogen": [9, 10], "hex": [], "hi": [7, 36, 37], "hidden": [1, 3, 4, 12, 21, 26, 37], "hidden_bia": [1, 39], "hidden_bias_gradi": [1, 38, 39], "hidden_deriv": 39, "hidden_func": 39, "hidden_layer_s": [0, 1, 31, 39], "hidden_neuron": 4, "hidden_nodes1": 39, "hidden_nodes2": 39, "hidden_weight": [1, 39], "hidden_weights_gradi": [1, 38, 39], "hierarch": [5, 32, 33], "high": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 13, 14, 21, 23, 24, 25, 31, 32, 33, 34, 35, 36, 39], "higher": [0, 1, 3, 5, 6, 8, 13, 18, 25, 31, 32, 33, 34, 35, 36, 39], "highest": [1, 2, 36, 37, 39], "highli": [0, 3, 4, 10, 19, 23, 24, 26, 30, 31, 32, 33, 34], "highlight": [], "highwai": [], "hing": 8, "hint": [13, 15, 16, 21, 22, 26, 32, 33], "hinton": 34, "hip": 23, "hire": 0, "hist": [4, 6, 7, 28, 35, 37], "histogram": [6, 7, 28, 37], "histor": [7, 11, 36], "histori": [3, 4, 12, 15, 34, 37, 38], "hitherto": 5, "hjorth": [29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "hobbi": 28, "hoc": [5, 32, 33], "hoff": 30, "hojjatk": 26, "hold": [1, 3, 6, 13, 14, 33, 34, 35, 39], "holder": [0, 31], "holdgraf_evidence_2014": [], "home": [], "homepag": [25, 26, 31], "homework": [6, 13, 33, 34], "homogen": [1, 3, 9, 10, 13, 34], "honchar": 2, "hopefulli": [0, 11, 15, 19, 28, 31, 34], "horizont": 11, "horlyk": [29, 31], "hornik": 38, "hors": [3, 7, 31, 36, 37], "hot": [1, 9, 36, 37, 39], "hour": [1, 23, 27, 28, 29, 31, 34, 35, 39], "how": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "howev": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "href": [], "hspace": [0, 4, 8, 10, 28, 31, 38, 39], "hstack": [1, 39], "htf": 31, "html": [0, 16, 20, 21, 23, 25, 26, 27, 29, 30, 31, 32, 33, 34, 38, 39], "http": [0, 3, 4, 6, 13, 15, 16, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "huang": [0, 31], "huber": [0, 31], "huge": [1, 3, 4, 23, 34, 39], "human": [0, 1, 3, 6, 9, 12, 32, 37, 38, 39], "humid": 9, "hundr": [1, 39], "hungri": [1, 39], "hybrid": 27, "hydrogen": [0, 31], "hyper": 26, "hyperbol": [1, 4, 12], "hyperparam": 8, "hyperparamat": 38, "hyperparamet": [3, 4, 5, 6, 9, 13, 18, 25, 26, 32, 33, 34, 38], "hyperplan": 11, "h\u00f8rlyk": [29, 31], "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, 28, 29, 30, 32, 33, 34, 35, 36, 37, 38], "i0": [0, 31], "i1": [0, 6, 8, 12, 31, 32, 34, 37], "i2": [0, 8, 12, 31, 37], "i3": [0, 12, 31, 37], "i5": [0, 31], "i_": [13, 33, 34], "i_1": [5, 6, 35], "i_2": [5, 6, 35], "i_siz": [21, 22], "i_t": 34, "ian": 30, "iayaan2": 21, "ic": [1, 25, 26, 39], "id": [7, 13, 33, 34, 36], "ida": [29, 31], "idea": [0, 1, 2, 3, 4, 6, 9, 10, 12, 13, 20, 24, 25, 26, 32, 33, 34, 35, 36, 37, 38, 39], "ideal": [0, 2, 6, 8, 13, 28, 31, 34, 35, 36, 37, 39], "idem": [6, 35, 36], "ident": [5, 6, 12, 13, 17, 18, 24, 32, 33, 37, 39], "identical": 35, "identifi": [0, 1, 7, 9, 11, 12, 13, 14, 31, 32, 36, 37, 39], "idx": [36, 37], "ieor": 28, "ifi": 30, "ifs": [23, 31], "ignor": [0, 1, 3, 9, 15, 32, 34, 39], "ii": [24, 28, 39], "iii": [24, 31, 39], "ij": [0, 1, 3, 6, 8, 12, 14, 16, 24, 28, 31, 32, 34, 37, 38, 39], "ik": [0, 24, 31, 32], "iki": [], "ilg3ggewq5u": [38, 39], "ill": 34, "illinoi": [], "illustr": [5, 7, 10, 12, 13, 14, 20, 23, 31, 36, 39], "ilsvrc": 34, "im": 6, "imag": [1, 3, 4, 6, 9, 11, 12, 14, 30, 31, 37, 38, 39], "image_at_epoch_": 4, "image_batch": 4, "image_height": 3, "image_path": [0, 6, 7, 9, 31, 35, 36], "image_width": 3, "imageio": 6, "imagenet": 34, "images_from_seed_imag": 4, "imagin": [1, 39], "immedi": [0, 3, 4, 6, 23, 31, 34], "implement": [0, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 19, 20, 21, 22, 25, 26, 28, 31, 32, 33, 34, 36, 37, 38], "impli": [3, 5, 6, 7, 13, 24, 32, 33, 34, 35, 36], "implicit": [3, 34], "implicitli": [11, 28], "import": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 25, 26, 28, 34, 35, 36, 37], "importantli": 3, "importerror": [], "impos": [0, 6, 11, 12, 31, 37, 39], "imposs": [0, 5, 31, 32, 33], "impract": 34, "impress": [0, 12, 31, 37, 38], "improv": [0, 4, 5, 9, 10, 11, 13, 15, 21, 25, 26, 32, 33], "impur": 9, "imread": 6, "imshow": [1, 3, 4, 6, 39], "in3050": [30, 31], "in3310": 31, "in4080": [30, 31], "in4300": [30, 31], "in4310": 30, "in5400": 3, "in5550": 30, "in_out_neuron": 4, "inaccur": [13, 33], "inact": [12, 37, 38, 39], "inadequ": [0, 31], "inappropri": 34, "inch": [6, 32], "incident": [], "includ": [0, 1, 2, 3, 4, 5, 6, 7, 11, 12, 15, 16, 17, 18, 19, 20, 21, 22, 23, 26, 28, 29, 30, 31, 32, 33, 35, 39], "include_bia": [6, 9, 35, 36], "incom": [12, 16, 37, 38], "incorrect": [1, 39], "incoveni": 8, "increas": [0, 1, 3, 4, 5, 6, 9, 12, 13, 19, 25, 28, 31, 32, 34, 35, 36, 37, 38, 39], "increasingli": 28, "increment": 34, "ind": 6, "inde": [0, 2, 4, 5, 6, 13, 31, 32, 33, 38], "indefinit": 4, "independ": [0, 5, 6, 7, 8, 12, 13, 28, 31, 32, 33, 34, 36, 37], "index": [0, 1, 3, 4, 10, 14, 23, 24, 25, 26, 28, 30, 31, 39], "index_col": [0, 31], "indic": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 16, 25, 26, 31, 32, 38, 39], "indirect": [], "indispens": [6, 35, 36], "individu": [1, 6, 7, 10, 12, 28, 31, 32, 34, 35, 36, 37, 38, 39], "indu": [], "indx": 24, "indx1": 2, "indx2": 2, "indx3": 2, "ineffici": [3, 13], "inequ": [8, 13], "inequaltii": 33, "inertia": 13, "inexperi": [], "inf": [], "inf1000": [23, 31], "inf1100": [23, 31], "inf1100l": [23, 31], "inf1110": [23, 31], "inf3000": 31, "infeas": [9, 34], "infer": [0, 1, 4, 6, 30, 31, 35, 36, 39], "inferenc": 1, "infil": [0, 6, 7, 9, 31, 35, 36], "infin": [5, 6, 7, 11, 19, 32, 33, 35, 36, 38, 39], "infinit": [3, 34], "infinitesim": 28, "influenc": [6, 10, 18, 35, 36], "influenti": [1, 39], "info": 31, "inform": [0, 1, 3, 4, 6, 9, 11, 12, 13, 14, 24, 25, 26, 30, 31, 33, 34, 35, 36, 37, 38, 39], "inforom": 15, "infrequ": 34, "infti": [3, 6, 13, 28, 33, 35, 38], "ingeni": [13, 33, 34], "ingredi": [0, 9, 31], "inher": [6, 34, 35, 36], "inherit": [24, 31, 34], "init": [], "initi": [0, 1, 2, 6, 10, 13, 14, 18, 24, 26, 28, 31, 33, 34, 35, 36, 37, 38, 39], "inititi": 39, "inject": 14, "inlin": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 24, 28, 31, 32, 33, 34, 35, 36, 37, 39], "inner": [0, 13, 32], "innerhtml": [], "inp": 4, "inplac": 13, "inpput": 38, "input": [0, 1, 3, 4, 5, 6, 7, 8, 12, 13, 14, 16, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37], "input_dim": 1, "input_nod": 39, "input_s": 21, "input_shap": [3, 4], "inputs": 1, "inputs_shuffl": [0, 1, 32, 39], "inquiri": 20, "insert": [3, 5, 6, 8, 10, 28, 32, 33, 35], "insid": [4, 7, 21, 37], "insight": [0, 1, 5, 23, 26, 31, 32, 33, 35, 36, 38], "insist": [6, 13, 32, 34], "inspir": [0, 1, 12, 25, 26, 31, 37, 38, 39], "instabl": 2, "instal": [0, 1, 5, 6, 9, 15, 20, 26, 39], "instanc": [0, 1, 2, 4, 6, 9, 11, 13, 16, 31, 32, 33, 34, 35, 36, 39], "instanti": 10, "instead": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 17, 20, 21, 22, 24, 28, 31, 32, 34, 35, 39], "institut": [1, 39], "instruct": [0, 1, 15, 39], "int": [0, 1, 2, 3, 4, 5, 6, 11, 13, 14, 24, 28, 32, 34, 35, 36, 37, 39], "int32": 10, "int_": [3, 6, 28, 35, 38], "int_0": 28, "int_a": 28, "intak": [0, 32], "integ": [1, 2, 13, 14, 24, 28, 31, 36, 37, 39], "integer_vector": [1, 39], "integr": [3, 6, 28, 31, 35], "intellig": [0, 14, 30, 31], "intend": 10, "intens": [1, 18, 39], "intention": 14, "interact": [0, 6, 9, 12, 23, 25, 26, 31, 37, 38], "intercept": [0, 6, 8, 11, 13, 16, 17, 18, 19, 31, 32, 33, 34, 35, 36, 37], "intercept_": [0, 6, 8, 9, 13, 31, 32, 34], "interchang": [5, 12, 24, 37, 38], "interconnect": [1, 39], "interesit": [], "interest": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 19, 23, 25, 26, 28, 31, 32, 33, 35, 36, 37, 38, 39], "interfac": [0, 1, 15, 24, 32, 39], "interior": [0, 9, 31], "intermedi": [24, 32, 34], "intermediari": [21, 22], "intermeti": 22, "intermetidari": 22, "intern": [1, 10, 12, 22, 36, 37, 38, 39], "internation": [], "interpol": [1, 3, 4, 6, 12, 37, 38, 39], "interpr": [5, 32, 33], "interpret": [0, 1, 6, 9, 10, 12, 13, 15, 16, 21, 24, 25, 26, 28, 38, 39], "interrupt": [], "interv": [0, 3, 5, 6, 7, 13, 19, 28, 31, 32, 33, 36, 37], "intial": [13, 33], "intract": [0, 4, 32], "intrins": [3, 11, 24, 28, 31], "intro": [23, 30, 31], "introduc": [0, 1, 5, 6, 8, 10, 12, 24, 25, 28, 31, 33, 34, 35, 37, 38, 39], "introduct": [1, 2, 4, 13, 30, 32, 33, 34, 36, 39], "introductori": [0, 4, 24, 30, 31, 32], "intuit": [0, 5, 6, 8, 12, 13, 25, 31, 34, 35, 36, 37, 38, 39], "inv": [0, 5, 13, 17, 31, 32, 33, 34], "invalid": [], "invalu": [0, 13, 23, 31, 33], "invari": [1, 39], "invd": 5, "inver": [8, 37], "invers": [0, 3, 6, 13, 31, 32, 33, 34], "inverse_transform": 8, "invert": [0, 5, 7, 10, 13, 16, 18, 31, 34, 36, 37], "investig": [], "invh": [13, 34], "invok": 8, "involv": [0, 2, 6, 7, 11, 12, 31, 32, 34, 35, 36, 37, 38, 39], "io": [0, 23, 25, 26, 27, 29, 30, 31, 32, 39], "ion": [], "ip": [0, 8, 28, 31], "ipca": 11, "ipynb": [23, 31], "ipython": [0, 5, 7, 9, 11, 14, 23, 25, 26, 31, 32, 36], "iq": [6, 35], "iri": [8, 9, 21], "irreduc": [6, 35, 36], "irrelev": [5, 32, 33], "irrespect": [0, 31], "irvin": [25, 26], "isaac": [], "isaacmus": [], "iseffici": [], "isn": 5, "isnan": 39, "isnul": [], "isolo": 22, "isomap": 11, "issu": [1, 9, 15, 24, 34, 39], "it_arrai": 13, "item": [0, 13, 31], "items": [24, 31], "iter": [1, 2, 4, 6, 8, 13, 14, 18, 25, 28, 33, 34, 35, 36, 37, 38, 39], "its": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 20, 21, 23, 24, 25, 26, 28, 31, 33, 34, 35, 36, 37, 38, 39], "itself": [5, 6, 12, 25, 26, 28, 31, 32, 35, 38], "iv": 39, "ix": 39, "j": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 24, 25, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "j1": 24, "j_": 6, "j_41hld6ttu": 35, "j_lasso_sk": 6, "j_ridge_sk": 6, "j_sk": 6, "jackknif": [6, 23, 31, 35, 36], "jacobian": [2, 13, 33], "janko": [], "jason": 4, "javascript": [], "jax": [23, 26, 31, 34, 38], "jeff": [], "jensen": [29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "jentzen": [38, 39], "jerom": [19, 25, 30], "jhauser": [], "ji": [12, 24, 38, 39], "jit": 13, "jj": [0, 5, 6, 31, 35], "jk": [0, 1, 6, 12, 24, 31, 37, 38, 39], "jl": [0, 31], "jm": 24, "jnp": 13, "job": [2, 8, 10, 15], "join": [0, 4, 6, 7, 9, 25, 26, 31, 35, 36], "joint": [4, 5], "jonathan": [], "json": [], "judg": [13, 33, 36, 37], "judgement": 6, "julia": [23, 24, 25], "juliu": [38, 39], "jump": [28, 34], "junk": 4, "jupit": 31, "jupyt": [0, 15, 16, 19, 23, 25, 30, 31, 35, 38, 39], "jupyterbook": [], "jupytext": [], "just": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20, 21, 22, 23, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "justif": 0, "justifi": [3, 10], "k": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 21, 23, 24, 25, 28, 29, 31, 32, 33, 34, 37], "k0": [7, 36, 37], "k1": [7, 36, 37], "kaggl": [6, 25, 26], "kajda": 39, "kappa_d": 28, "karl": [29, 31], "karush": 8, "katex": [], "katrin": [29, 31], "keep": [0, 1, 4, 5, 6, 11, 13, 14, 15, 18, 21, 22, 24, 25, 26, 31, 32, 33, 34, 35, 36, 39], "keepdim": [1, 6, 10, 24, 35, 36, 37, 39], "kei": [1, 3, 6, 12, 34, 37, 39], "kellei": [], "kenneth": [], "kept": [4, 6, 14, 35, 36], "kera": [0, 4, 23, 25, 26, 31], "kernel": [0, 1, 3, 23, 31, 32, 39], "kernel_regular": [1, 3, 39], "kernel_s": 4, "kernelpca": 11, "kev": [0, 31], "kevin": [30, 31], "kevinsheppard": [], "keyboardinterrupt": 39, "keyword": [18, 24, 31, 39], "kfold": [6, 35, 36], "kg": [1, 39], "ki": 24, "kick": [1, 13, 34, 39], "kiener": 2, "kilomet": [6, 32], "kim": [], "kind": [0, 2, 3, 4, 8, 12, 13, 14, 31, 32, 37, 38, 39], "kingma": 34, "kj": [6, 12, 24, 32, 34, 38, 39], "kjm": [23, 31], "kkt": 8, "kl": 28, "km": [12, 31, 37], "kmean": 14, "kmeanspoint": 14, "kn_k": 14, "know": [0, 1, 2, 5, 6, 8, 13, 15, 16, 17, 19, 20, 23, 31, 32, 33, 39], "knowledg": [0, 23, 31], "known": [1, 3, 4, 5, 6, 7, 8, 9, 12, 18, 24, 25, 26, 28, 30, 32, 34, 35, 36, 37, 38, 39], "kondev": [0, 31], "kp": 28, "kpca": 11, "kramdown": [], "kroneck": 14, "kt": [], "kuckuck": [38, 39], "kuhn": 8, "kutyniok": [38, 39], "kvalsund": [29, 31], "kwarg": 39, "kwown": [0, 31], "l": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 22, 24, 25, 28, 31, 33, 34, 36, 37], "l0": [7, 36, 37], "l1": [0, 1, 3, 7, 31, 36, 37, 39], "l1_l2": [1, 3, 39], "l1regl": 5, "l2": [1, 3, 39], "l_": [24, 34], "l_1": [7, 26, 36, 37, 38], "l_2": [7, 13, 26, 33, 34, 36, 37, 38], "l_i": 34, "l_j": [12, 38, 39], "l_ja": 39, "la": 13, "la_": [], "la_i": [12, 38, 39], "la_k": [12, 38], "lab": [20, 23, 25, 26, 31], "label": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 20, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "labelencod": [7, 10, 37], "labels": [6, 8, 9], "labels_shuffl": [0, 1, 32, 39], "laboratori": 27, "lack": [0, 31, 34], "lagari": 2, "lagrang": [8, 11], "lam": [18, 39], "lambda": [0, 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 17, 18, 19, 20, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 39], "lambda_": 11, "lambda_0": 11, "lambda_1": [5, 8, 11, 32, 33], "lambda_2": [8, 11], "lambda_i": [8, 11], "lambda_iy_i": 8, "lambda_jy_iy_j": 8, "lambda_k": 8, "lambda_n": [5, 8, 32, 33], "lamda": 1, "land": 8, "landmark": 8, "landscap": [13, 18, 33, 34], "langl": [0, 6, 11, 28, 31, 32], "languag": [0, 1, 4, 8, 23, 24, 25, 26, 30, 31, 39], "lapack": [24, 31], "laplac": 5, "laptop": [15, 23], "larg": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 13, 18, 23, 24, 25, 28, 30, 31, 32, 33, 34, 35, 36, 38, 39], "larger": [0, 3, 5, 6, 8, 10, 11, 13, 17, 22, 28, 31, 32, 33, 34, 35], "largest": [4, 8, 11], "lasso": [0, 7, 23, 26, 31, 34, 35, 36, 37], "lasso_sk": 6, "last": [0, 1, 3, 4, 5, 6, 7, 8, 12, 16, 17, 19, 21, 22, 24, 25, 28, 29, 31, 33, 35, 36], "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, 22, 23, 25, 26, 31, 34, 36, 37, 38, 39], "latest": [4, 15, 23], "latest_checkpoint": 4, "latex": [20, 31], "latexcodec": [], "latrpygrtttbnjr3znuhl": 22, "latter": [0, 3, 6, 7, 8, 11, 13, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38], "lattic": [12, 37, 38], "law": 0, "layer": [0, 4, 13, 26, 31, 34, 37], "layer_grad": 22, "layer_input": 22, "layer_output_s": [21, 22], "layers_grad": 21, "lbfg": [7, 9, 10, 37], "lc_messag": [], "lcc": [5, 6, 35], "lda": 11, "ldot": [0, 6, 11, 25, 31, 35, 36], "le": [5, 7, 10, 13, 17, 28, 32, 33, 34, 36], "lead": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "leaf": 9, "leaki": [1, 26, 39], "leakyrelu": 4, "lear": [13, 33], "learn": [3, 4, 5, 6, 7, 8, 9, 10, 12, 21, 24, 29, 30], "learnabl": 3, "learner": 10, "learnig": 31, "learning_r": [8, 10, 21], "learning_rate_init": [0, 1, 31, 39], "learning_schedul": [13, 34], "learnt": [25, 26], "least": [0, 7, 8, 10, 11, 17, 18, 23, 24, 28, 35, 36, 37], "leat": [13, 34], "leav": [0, 1, 3, 5, 6, 9, 11, 21, 31, 33, 35, 36, 39], "lectur": [0, 1, 5, 10, 11, 12, 13, 23, 24, 25, 26, 27, 29, 30, 32], "lecturenot": [0, 23, 25, 26, 30, 31, 39], "left": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "leftarrow": [8, 12, 38, 39], "legend": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 15, 21, 31, 32, 33, 34, 35, 36, 37], "legend_el": 21, "leinonen": 31, "len": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 16, 17, 21, 22, 24, 31, 32, 33, 34, 35, 36, 37, 39], "length": [0, 1, 3, 4, 8, 9, 13, 16, 21, 23, 31, 32, 33, 34, 39], "length_of_sequ": 4, "leq": [0, 5, 7, 8, 13, 14, 28, 31, 32, 33, 34, 36], "less": [0, 1, 3, 4, 5, 6, 8, 9, 13, 23, 28, 31, 32, 33, 34, 35, 36, 39], "lessen": [1, 39], "let": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 19, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "letter": [0, 16, 24, 28, 31, 32], "level": [0, 1, 5, 6, 9, 23, 24, 25, 26, 27, 29, 31, 34, 35, 36, 38, 39], "leverag": 34, "lexer": [], "li": [8, 11], "liabil": [], "liabl": [], "lib": [], "liberti": 34, "liblinear": 10, "librari": [0, 1, 2, 3, 4, 5, 6, 9, 10, 11, 24, 25, 28, 30, 32, 33, 34, 39], "licenc": [], "licens": [0, 1, 23, 25, 31, 39], "lie": [0, 6, 11, 28, 31, 32, 35, 36], "life": [0, 1, 8, 12, 31, 37, 38, 39], "lifetim": 13, "light": [], "like": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 16, 20, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "likelihood": [0, 1, 5, 9, 31, 32, 39], "lim_": 28, "limit": [0, 5, 6, 8, 12, 24, 25, 26, 31, 32, 36, 37, 38], "lin_clf": 8, "lin_model": [], "lin_reg": 9, "linalg": [0, 2, 5, 6, 8, 11, 13, 17, 24, 28, 31, 32, 33, 34, 37], "line": [0, 3, 6, 8, 11, 13, 15, 16, 20, 21, 31, 33, 34, 35, 38, 39], "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, 28, 34, 35, 37, 38, 39], "linear_model": [0, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 26, 31, 32, 33, 34, 35, 36, 37], "linear_regress": [6, 35, 36, 39], "linearli": [5, 32, 33, 34], "linearloc": [6, 13, 33, 34], "linearregress": [0, 6, 7, 9, 15, 16, 19, 31, 32, 34, 35, 36], "linearsvc": 8, "lineat": 33, "liner": [1, 3, 39], "linerar": 10, "linewidth": [0, 2, 4, 6, 8, 9, 10, 35], "link": [0, 4, 9, 12, 15, 20, 21, 23, 25, 26, 27, 29, 31, 36, 38], "linlag": 5, "linpack": [24, 31], "linreg": [0, 31], "linspac": [0, 2, 3, 4, 6, 8, 9, 10, 13, 16, 17, 19, 24, 28, 31, 32, 34, 35, 36], "linu": 4, "linux": [0, 1, 23, 25, 31, 39], "liquid": [0, 31], "list": [1, 2, 3, 4, 9, 15, 21, 22, 23, 25, 26, 31, 34, 37], "listedcolormap": [9, 10], "literatur": [1, 7, 14, 30, 35, 36, 39], "littl": [1, 3, 9, 12, 22, 34, 38, 39], "live": [8, 16], "ll": [0, 18, 28, 31, 32], "lle": [0, 32], "llm": 20, "lloyd": [4, 14], "lmb": [0, 2, 5, 6, 32, 33, 34, 35, 36], "lmbd": [0, 1, 3, 31, 39], "lmbd_val": [0, 1, 3, 31, 39], "lmbda": [13, 33, 34], "ln": [1, 13, 33, 39], "load": [1, 4, 6, 7, 9, 10, 34, 37], "load_boston": [], "load_breast_canc": [1, 7, 9, 10, 11, 37, 39], "load_data": [3, 4], "load_digit": [1, 3, 39], "load_iri": [8, 9, 21], "loc": [3, 6, 7, 8, 9, 10, 21, 31, 35, 36, 37], "local": [0, 1, 3, 7, 12, 13, 15, 21, 22, 32, 33, 34, 36, 37, 38, 39], "locat": [2, 3, 8, 15], "log": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 13, 15, 20, 21, 24, 25, 26, 31, 34, 35, 36, 37, 39], "log10": [0, 5, 6, 32, 33, 34, 35, 36, 39], "log_": [0, 31], "log_clf": 10, "logarithm": [0, 5, 7, 17, 24, 31, 35, 36, 37], "logbook": [25, 26], "logic": [0, 1, 9, 31, 39], "logical_or": [], "login": 15, "logist": [0, 1, 2, 8, 9, 10, 11, 12, 13, 23, 26, 32, 33, 34, 38], "logisti": 26, "logistic_regress": 39, "logisticregress": [7, 9, 10, 11, 26, 36, 37], "logit": [7, 26, 36, 37], "logreg": [7, 9, 10, 11, 37], "logspac": [0, 1, 3, 5, 6, 31, 32, 33, 34, 35, 36, 39], "long": [0, 1, 3, 4, 12, 13, 21, 31, 33, 34, 37, 38, 39], "longer": [2, 3, 8, 10, 14, 24, 28, 31, 34], "loocv": [6, 35, 36], "look": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 19, 20, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 39], "loop": [1, 4, 6, 10, 12, 14, 16, 17, 18, 22, 23, 24, 31, 34, 35, 36, 39], "lose": [1, 39], "loss": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 13, 18, 21, 24, 25, 26, 31, 35, 36, 37, 38, 39], "loss_bin": [36, 37], "loss_fil": 4, "loss_multi": [36, 37], "loss_vec": [36, 37], "lossfil": 4, "lost": 4, "lot": [1, 4, 6, 16, 19, 20, 34, 35, 39], "low": [0, 6, 9, 10, 11, 25, 31, 32, 35, 36], "lower": [0, 1, 3, 6, 9, 10, 16, 21, 24, 32, 34, 39], "lowercas": [24, 31], "lowest": [9, 13, 28, 34], "lr": [1, 3, 4, 10, 36, 37, 39], "lrelu": 39, "lstat": [], "lstm": 4, "lstm_2layer": 4, "lstsq": [0, 31, 32], "lt": [6, 35], "lu": [0, 5, 31, 32, 33], "lubksb": 24, "luckili": 2, "ludcmp": 24, "lux": 24, "lvert": [1, 39], "lw": [0, 31], "m": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 15, 24, 28, 29, 30, 31, 32, 33, 34, 35, 37, 38, 39], "m_": [9, 12, 38, 39], "m_0": 34, "m_1": 14, "m_h": [0, 31], "m_k": 14, "m_l": [12, 38, 39], "m_n": [0, 31], "m_p": [0, 31], "m_t": [13, 34], "ma": 11, "machin": [1, 3, 4, 5, 6, 7, 9, 10, 11, 12, 15, 16, 24, 30, 32, 34, 35, 38, 39], "machinelearn": [0, 6, 16, 20, 23, 25, 26, 27, 29, 30, 31, 32, 33, 36, 37, 39], "machineri": [], "mackai": 30, "macro": [], "made": [0, 1, 3, 4, 5, 6, 7, 9, 11, 12, 25, 26, 31, 32, 34, 36, 37, 38, 39], "mae": [0, 31], "magic": 4, "magnitud": [1, 6, 7, 13, 21, 32, 34, 37, 38, 39], "mai": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 13, 19, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "mail": [27, 29], "main": [0, 1, 3, 4, 5, 6, 7, 9, 24, 25, 26, 30, 32, 33, 34, 36, 37, 39], "mainli": [0, 5, 6, 7, 9, 31, 32, 35, 36, 37], "maintain": [6, 34, 35], "major": [1, 6, 9, 10, 13, 24, 31, 33, 34, 35, 36, 39], "make": [1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 15, 16, 18, 19, 21, 22, 23, 24, 25, 26, 28, 30, 31, 33, 34, 35, 36, 37, 38, 39], "make_axes_locat": 6, "make_classif": 37, "make_moon": [8, 9, 10], "make_pipelin": [0, 6, 10, 32, 35, 36], "makedir": [0, 6, 7, 9, 31, 35, 36], "malcondit": 24, "malign": [1, 7, 9, 37], "mammographi": 5, "manag": [0, 2, 3, 15, 23, 25, 31, 34], "mandatori": [29, 31], "mani": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "manifold": 11, "manner": 3, "manual": [6, 21, 22, 32, 34], "map": [0, 1, 2, 6, 7, 8, 11, 12, 14, 28, 31, 36, 37, 39], "marc": 32, "marchant": [], "margin": [0, 5, 8], "marit": [0, 31], "mark": 31, "markdownfil": [], "markdownit": [], "markdownitdeflist": [], "markedli": [], "marker": [7, 24, 31, 36], "markov": [23, 31], "markup": [], "marsaglia": 28, "mask_or": [], "masked_arrai": [], "maskedrecord": [], "mass": [0, 1, 5, 13, 32, 33, 39], "massag": [0, 31], "masses2016": [0, 31], "masses2016ol": [0, 31], "masses2016tre": 0, "masseval2016": [0, 31], "master": [27, 29], "mat": [23, 31], "mat1100": [23, 31], "mat1110": [23, 31], "mat1120": [23, 31], "match": [1, 4, 5, 13, 14, 15, 32, 33, 34, 39], "materi": [4, 5, 7, 13, 15, 24, 27, 29, 37], "math": [3, 7, 12, 13, 24, 28, 30, 31, 34, 36, 37, 39], "mathbb": [0, 4, 5, 6, 7, 8, 11, 12, 13, 14, 17, 19, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38], "mathbf": [0, 5, 6, 7, 8, 13, 19, 24, 25, 31, 32, 33, 34, 35, 36, 37, 38], "mathcal": [1, 5, 6, 7, 13, 25, 35, 36, 37, 39], "matheemat": 3, "mathemat": [0, 6, 11, 12, 13, 21, 23, 24, 28, 30, 31, 34], "mathemati": 31, "mathrm": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "matmul": [1, 2, 5, 38, 39], "matnat": 30, "matplotlib": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 23, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 39], "matplotlibrc": [], "matric": [0, 1, 3, 4, 6, 7, 8, 11, 13, 16, 17, 23, 32, 33, 36, 37, 38, 39], "matrix": [0, 2, 3, 4, 6, 7, 8, 10, 13, 17, 18, 19, 21, 25, 26, 28, 35, 36, 38], "matshow": 1, "matter": [2, 3, 13, 32, 33, 34, 38], "matthia": [], "max": [0, 1, 2, 3, 4, 9, 10, 12, 13, 21, 29, 31, 33, 34, 36, 37, 38, 39], "max_depth": [0, 9, 10], "max_diff": 2, "max_diff1": 2, "max_diff2": 2, "max_it": [0, 1, 8, 13, 26, 31, 37, 39], "max_iter": 14, "max_leaf_nod": 10, "max_sampl": 10, "maxdegre": [0, 6, 10, 32, 35, 36], "maxdepth": 10, "maxim": [1, 4, 5, 7, 8, 11, 35, 36, 37, 39], "maximum": [0, 2, 3, 5, 7, 8, 9, 10, 13, 14, 31, 32, 33, 34], "maxpolydegre": [5, 6, 32, 33, 34, 35, 36], "maxpooling2d": 3, "mbox": [5, 6, 32, 33, 35], "mcculloch": [12, 37, 38], "md": 11, "mdoel": 4, "me": [], "mean": [1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 28, 31, 34, 35, 37, 38, 39], "mean0": [36, 37], "mean1": [36, 37], "mean_absolute_error": [0, 31], "mean_divisor": 14, "mean_i": 28, "mean_matrix": 14, "mean_squared_error": [0, 4, 6, 7, 10, 15, 19, 31, 32, 35, 36], "mean_squared_log_error": [0, 31], "mean_vector": 14, "mean_x": 28, "meaning": [0, 4, 7, 31, 36], "meansquarederror": [0, 31], "meant": [3, 7, 10, 13, 36, 38], "meanwhil": 34, "measur": [0, 1, 2, 5, 6, 9, 11, 12, 14, 16, 18, 25, 26, 28, 31, 32, 34, 35, 36, 38, 39], "mechan": [0, 4, 28, 31, 34], "median": [0, 31, 32, 34], "medicin": [12, 37, 38], "medium": [4, 8, 13, 26, 34], "medv": [], "meet": [0, 29], "mehta": [0, 31, 32, 33], "member": [20, 25, 26], "memori": [3, 4, 11, 12, 13, 18, 24, 37, 38], "mentat": [], "mention": [0, 12, 13, 25, 26, 28, 31, 33, 34, 37, 38], "merchant": [], "mere": [0, 25, 26], "merg": [], "meshgrid": [2, 5, 6, 8, 9, 10, 11, 39], "mess": 15, "messag": [5, 13], "messi": 2, "messier": 22, "met": [0, 3, 8, 32], "meta": [], "meteorolog": 9, "meter": [6, 32], "method": [0, 1, 2, 3, 4, 5, 7, 8, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 26, 28, 30, 32, 38], "metion": 6, "metric": [0, 1, 3, 6, 7, 9, 10, 14, 15, 21, 22, 26, 31, 32, 35, 36, 37, 39], "metropoli": [23, 31], "mev": [0, 28, 31], "mgd": [13, 34], "mglearn": [23, 31], "mgrid": 13, "mhjensen": [], "mi": 10, "mia": [29, 31], "michael": [26, 38, 39], "microsoft": 30, "mid": [1, 39], "midel": 4, "midnight": [15, 21, 22], "midpoint": 9, "might": [0, 1, 2, 4, 6, 9, 13, 15, 17, 18, 22, 32, 33, 34, 39], "migth": 17, "mild": 9, "millimet": [6, 32], "million": [0, 31, 32, 34], "mimic": [12, 37, 38], "min": [0, 2, 5, 8, 9, 33], "min_": [0, 2, 5, 14, 17, 31, 32, 33], "min_samples_leaf": 9, "mind": [0, 6, 13, 15, 18, 21, 31, 32, 33, 34, 35], "mindboard": 4, "mine": [23, 31], "mini": [1, 11, 12, 13, 33, 39], "minibatch": [1, 11, 13, 39], "minibathc": [13, 34], "miniforge3": [], "minim": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 32, 33, 34, 35, 39], "minima": [0, 1, 7, 13, 31, 33, 34, 36, 37, 39], "minimum": [0, 1, 2, 6, 8, 9, 11, 13, 32, 33, 34, 35, 36, 37, 39], "minmaxscal": [0, 32, 34, 39], "minor": 28, "minst": [1, 39], "minu": [7, 36], "mirjalili": 31, "mirror": 9, "misc": 6, "misclassif": [8, 9, 10], "misclassifi": [8, 10], "miser": 0, "mismatch": [1, 39], "miss": [7, 10], "mistak": [4, 19], "mit": 30, "mitig": 34, "mix": [1, 2, 31, 39], "mixtur": [13, 34], "mk": [9, 24], "mkdir": [0, 6, 7, 9, 31, 35, 36], "ml": [0, 1, 10, 13, 24, 25, 26, 32, 33, 34, 39], "mlab": 28, "mle": [5, 7, 36, 37], "mlp": [1, 37, 38, 39], "mlpclassifi": [1, 37, 39], "mlpregressor": [0, 31], "mm": 24, "mml": 32, "mn": [12, 28, 37], "mnist": [1, 11, 26, 39], "mnist_784": 26, "mo": [], "mod": 28, "mode": [27, 29, 31, 36, 37, 39], "model": [2, 3, 5, 7, 8, 9, 10, 11, 13, 14, 16, 18, 19, 20, 21, 23, 25, 26, 28, 30, 32, 33, 34, 35, 36], "model_bin": [36, 37], "model_multi": [36, 37], "model_select": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 26, 31, 32, 33, 34, 35, 36, 37, 39], "moder": [10, 34], "modern": [0, 6, 7, 23, 31, 34, 35, 36, 37, 38, 39], "modest": 34, "modif": [2, 12, 13], "modifi": [0, 1, 3, 5, 7, 8, 10, 12, 13, 31, 32, 33, 34, 36, 37, 38, 39], "modul": [0, 16, 24, 31], "modular": 28, "modulo": 28, "moe": [11, 32], "moment": [5, 6, 13, 28, 35, 39], "moment_correct": 39, "momentum": [22, 38, 39], "momentum_schedul": 39, "mondai": [29, 31, 36], "monitor": [13, 34], "monoton": [5, 12, 28, 35, 37, 38, 39], "mont": [0, 6, 23, 28, 30, 31, 35, 36], "montli": 16, "moor": [5, 6], "more": [0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 21, 22, 23, 26, 28], "moreov": [0, 3, 26], "morten": [29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "mortenhj": 31, "most": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 21, 22, 23, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "mostli": [1, 11, 18, 34, 39], "motion": [0, 13], "motiv": [1, 4, 38, 39], "moulin": 34, "move": [0, 4, 5, 6, 7, 9, 12, 13, 14, 15, 16, 21, 22, 25, 28, 32, 33, 35, 36, 37, 38, 39], "mpl": [7, 31, 36], "mpl_toolkit": [2, 6, 13, 33, 34], "mplot3d": [2, 6, 13, 33, 34], "mplregressor": [1, 39], "mr_": [], "mrecord": [], "ms3tv8fvar": 37, "mse": [0, 4, 5, 6, 9, 10, 15, 16, 17, 19, 20, 22, 25, 26, 31, 32, 33, 34, 35, 36, 39], "mse_der": 22, "mse_simpletre": 10, "mselassopredict": [5, 33], "mselassotrain": [5, 33], "mseownridgepredict": [6, 32, 33, 34], "msepredict": [5, 33], "mseridgepredict": [0, 5, 6, 32, 33, 34], "msetrain": [5, 33], "msg": [], "msle": [0, 31], "mt": [7, 12, 36, 37, 39], "mu": [0, 6, 11, 13, 28, 31, 34, 35], "mu0": 28, "mu1": 28, "mu2": 28, "mu_": [6, 28, 32, 34, 35], "mu_i": [6, 32, 34], "mu_n": 11, "mu_x": 28, "much": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 15, 20, 21, 22, 24, 25, 28, 31, 32, 33, 34, 35, 36, 38, 39], "multi": [0, 1, 3, 7, 23, 31, 36], "multi_class": [26, 36, 37], "multiclass": [1, 7, 26, 36, 37], "multiclass_result": [36, 37], "multidimension": [11, 12, 31, 37, 38], "multilay": [1, 39], "multinomi": [7, 26, 36, 37], "multipl": [2, 4, 5, 6, 7, 12, 13, 15, 22, 28, 32, 33, 34, 35, 36, 37, 38], "multipli": [3, 5, 6, 11, 13, 18, 22, 24, 28, 32, 33, 34], "multiplum": 8, "multivari": [0, 2, 10, 11, 23, 28, 31], "multivariate_norm": [11, 14], "multpli": 16, "murphi": [11, 30, 31], "muse": [], "must": [1, 2, 5, 6, 8, 10, 12, 13, 14, 15, 20, 22, 25, 26, 28, 32, 33, 34, 35, 36, 37, 38, 39], "mutat": [7, 36, 37], "mutual": [1, 3, 6, 13, 35, 36, 39], "mx_": 28, "my": 31, "myenv": [], "myriad": [0, 23, 31], "myself": [], "mz1": 28, "mz2": 28, "m\u00f8svatn": 6, "n": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "n0": [36, 37], "n1": [24, 36, 37], "n2": 24, "n8grai": [], "n_": [1, 2, 3, 8, 12, 28, 37, 39], "n_0": [12, 28, 37], "n_boostrap": [6, 10, 35, 36], "n_bootstrap": [6, 35], "n_categori": [1, 3, 39], "n_class": [36, 37], "n_cluster": 14, "n_compon": 11, "n_epoch": [13, 34, 39], "n_estim": 10, "n_examples_to_gener": 4, "n_featur": [1, 18, 36, 37, 38, 39], "n_filter": 3, "n_hidden": 2, "n_hidden_neuron": [0, 1, 31, 38, 39], "n_i": 28, "n_input": [0, 1, 3, 32, 38, 39], "n_instanc": 9, "n_iter": 34, "n_job": 10, "n_k": 14, "n_l": [12, 28, 37], "n_layer": 1, "n_m": 9, "n_neuron": 1, "n_neurons_connect": 3, "n_neurons_layer1": [1, 39], "n_neurons_layer2": [1, 39], "n_output": [38, 39], "n_point": 14, "n_sampl": [6, 8, 9, 10, 14, 18, 35, 36, 37], "n_split": [6, 35, 36], "n_step": 4, "n_t": 2, "n_x": 2, "nabla": [1, 13, 33, 34, 39], "nabla_": [2, 13, 33, 34], "nabla_w": 13, "nafter": 39, "nag": 13, "naimi": [0, 31], "naiv": [7, 36, 37], "naive_kmean": 14, "name": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 18, 20, 21, 23, 24, 25, 26, 28, 29, 31, 32, 33, 35, 36, 37, 38, 39], "namespac": [], "nan": 39, "narrow": [13, 34], "nathaniel": [], "nation": [1, 5, 39], "nativ": [23, 31], "natur": [0, 1, 4, 8, 9, 12, 13, 25, 26, 28, 30, 31, 33, 34, 37, 38, 39], "navier": [12, 37, 38], "navig": [15, 34], "nb": 28, "nb_": 24, "nbconvert": 31, "nd": 14, "ndarrai": [6, 39], "nderiv": 39, "ne": [9, 10, 24, 28, 32, 33], "nearest": [1, 3, 6, 11, 39], "nearli": [13, 33], "neat": 31, "neccesari": [6, 35], "necess": 2, "necessari": [0, 1, 3, 4, 8, 14, 18, 31, 38, 39], "necessarili": [0, 4, 11, 28, 31], "necesserali": 5, "neck": [7, 36, 37], "need": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, 22, 24, 26, 28, 32, 33, 34, 35, 36, 37, 38, 39], "neg": [0, 1, 3, 5, 6, 7, 10, 13, 24, 28, 31, 33, 35, 36, 37, 39], "neg_mean_squared_error": [6, 35, 36], "neglect": [28, 34], "neglig": 28, "neighbor": [3, 6, 11], "neither": [4, 13, 34], "neq": [13, 14, 28, 33], "nerual": 39, "nervou": [12, 37, 38], "nest": [9, 12, 37], "nesterov": 13, "net": [2, 4, 12, 37, 38], "netlib": [24, 31], "network": [0, 9, 13, 21, 22, 23, 30, 32], "network_input_s": [21, 22], "neural": [0, 13, 21, 22, 23, 30, 32, 36], "neural_network": [0, 1, 2, 31, 37, 39], "neuralnetwork": [1, 22, 39], "neuralnetworksanddeeplearn": [26, 38, 39], "neuron": [1, 2, 3, 4, 12, 39], "neutral": [0, 31], "neutron": [0, 31], "never": [1, 4, 6, 9, 28, 35, 36, 39], "new": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 20, 22, 24, 31, 32, 33, 34, 36, 37, 39], "new_chang": [13, 34], "new_hobbit": 31, "new_ma": [], "newaxi": [0, 3, 6, 9, 21, 35, 36], "newli": [0, 31], "newlin": [36, 37], "newton": [1, 7, 8, 13, 28, 38, 39], "next": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 21, 22, 31, 32, 33, 34, 35, 37, 38, 39], "next_guess": 13, "next_input": 4, "ng": [1, 39], "nhow": 39, "ni": 14, "nice": [0, 1, 5, 11, 22, 31, 32, 33, 39], "nicer": [18, 34], "nielsen": [26, 38, 39], "nine": [38, 39], "nip": 34, "niter": [13, 33, 34], "nitric": [], "nlambda": [0, 5, 6, 32, 33, 34, 35, 36], "nlp": 30, "nm": 28, "nm_n": [0, 31], "nmse": [6, 35, 36], "nn": [2, 5, 6, 12, 24, 31, 35, 37], "nn_model": 1, "nnmin": 2, "node": [1, 3, 9, 10, 12, 21, 26, 37], "nois": [0, 4, 5, 6, 8, 9, 10, 13, 18, 19, 25, 31, 32, 33, 34, 35, 36], "noise_dimens": 4, "noisi": [1, 6, 25, 34, 35, 36, 39], "nomask": [], "non": [0, 1, 3, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 21, 24, 28, 31, 32, 33, 35, 36, 37, 38, 39], "nondifferenti": 34, "none": [0, 1, 2, 4, 5, 9, 10, 13, 28, 31, 32, 36, 37, 38, 39], "noninfring": [], "nonlinear": [3, 6, 8, 9, 11, 12, 35, 36, 37, 38], "nonneg": [6, 9, 13, 33, 35, 36], "nonparametr": 6, "nonsens": 28, "nonsingular": 24, "nonumb": [3, 7, 8, 13, 24, 36, 37], "nor": [1, 4, 13, 22, 34, 38, 39], "norm": [0, 1, 5, 6, 8, 11, 13, 18, 31, 32, 33, 34, 35, 38, 39], "normal": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 21, 23, 24, 25, 26, 28, 31, 32, 33, 34, 36, 37, 38], "normali": [24, 31], "norwai": [6, 25, 26, 31, 33, 34, 35, 37, 38, 39], "notabl": [], "notat": [0, 2, 5, 6, 13, 14, 28, 31, 32, 33, 35, 36, 38, 39], "note": [0, 1, 2, 3, 4, 5, 6, 7, 8, 11, 12, 13, 14, 15, 16, 18, 22, 23, 24, 28, 30, 31, 34, 35, 36, 37, 38, 39], "notebook": [0, 1, 3, 9, 15, 16, 19, 20, 21, 22, 23, 25, 26, 31, 35, 38, 39], "noteworthi": 34, "noth": [1, 2, 5, 8, 12, 14, 28, 32, 33, 37, 39], "notic": [4, 5, 12, 13, 22, 24, 28, 31, 38, 39], "notimplementederror": 39, "notion": 3, "noutput": 39, "novel": [3, 6, 10, 31], "novemb": [1, 29, 31, 39], "now": [0, 2, 4, 5, 6, 7, 8, 10, 11, 12, 14, 15, 16, 19, 21, 22, 23, 24, 25, 26, 28, 31, 32, 37, 38, 39], "nowadai": [0, 1, 3, 9, 23, 31, 39], "nox": [], "np": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "npm": [], "npr": 2, "nsampl": [6, 35, 36], "nt": 2, "nu": 28, "nuclear": [5, 32, 33], "nuclei": [0, 28, 31], "nucleon": [0, 31], "nucleu": [0, 31], "num": 4, "num_coordin": 2, "num_equ": 39, "num_hidden_neuron": 2, "num_it": [2, 18], "num_neuron": 2, "num_neurons_hidden": 2, "num_not": 39, "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, 21, 24, 25, 26, 27, 29, 31, 33, 35, 36, 37, 39], "numberid": [7, 36], "numberparamet": 3, "numer": [0, 5, 6, 9, 10, 11, 12, 13, 21, 23, 24, 30, 31, 32, 33, 34, 35, 36, 37, 38], "numpi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 25, 28, 32, 33, 34, 35, 36, 37, 38, 39], "numpydocstr": [], "nunmpi": [5, 32], "nve_frngahw": 33, "nx": 2, "ny": [28, 39], "o": [0, 1, 4, 5, 6, 7, 8, 9, 11, 24, 29, 30, 31, 32, 33, 34, 35, 36, 37], "obei": [6, 11, 13, 32, 34], "object": [0, 1, 4, 8, 10, 15, 19, 24, 31, 34, 38], "obliqu": [5, 32, 33], "observ": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 28, 31, 33, 34, 35, 36, 37], "obtain": [0, 1, 5, 6, 7, 8, 9, 10, 12, 13, 14, 17, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "obviou": [5, 6, 11, 28, 32, 33], "obviouli": 31, "obvious": [0, 4, 5, 6, 24, 31, 35], "oc": [32, 33], "occupi": [], "occur": [0, 6, 8, 9, 24, 28, 31], "octob": [21, 22, 26, 29, 31, 37], "od": 0, "odd": [0, 3, 7, 31, 32, 34, 36, 37], "odenum": 2, "odesi": 2, "oen": 0, "off": [1, 3, 4, 5, 9, 13, 20, 26, 28, 34, 35, 39], "offer": [6, 11, 23, 24, 27, 29, 31, 35, 36], "offic": [29, 31], "offici": [27, 31], "offlin": [21, 22], "often": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "ofter": [24, 31], "og": 39, "ol": [0, 13, 17, 19, 26, 32, 34, 36], "old": [1, 5, 10, 13, 15, 18, 36, 37, 39], "old_ma": [], "oliph": [], "ols_paramet": 16, "ols_sk": 6, "ols_svd": 6, "olsbeta": 33, "olstheta": [0, 5], "omega": [2, 3, 6], "omega_0": 3, "omit": [0, 5, 31, 32, 33, 35], "onc": [1, 6, 9, 11, 13, 20, 35, 36, 39], "one": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 19, 20, 21, 23, 24, 25, 26, 28, 29, 31, 32, 34, 35, 36, 37], "one_hot": [36, 37], "one_hot_predict": 21, "onehot": [1, 39], "onehot_vector": [1, 39], "onehotencod": 9, "ones": [0, 2, 5, 6, 8, 9, 10, 11, 13, 16, 18, 21, 22, 24, 25, 31, 32, 33, 34, 35, 36, 38], "ones_lik": 4, "ong": 32, "onl": 3, "onli": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "onlin": [11, 15, 20, 27, 34, 38, 39], "onto": [5, 11, 32, 33], "open": [0, 1, 4, 6, 7, 9, 15, 23, 25, 27, 29, 31, 35, 36, 37, 39], "oper": [0, 1, 3, 5, 6, 10, 11, 12, 13, 15, 16, 21, 22, 23, 28, 31, 32, 33, 34, 35, 37, 39], "operation": 28, "oplu": 28, "opmiz": [13, 34], "opportun": 0, "oppos": [6, 13], "opposit": [1, 5, 8, 32, 33, 39], "opt": [1, 5, 25, 26, 31, 33, 39], "optim": [0, 2, 3, 4, 5, 6, 7, 9, 10, 11, 14, 16, 17, 19, 21, 22, 25, 26, 35], "optimis": [1, 3, 39], "option": [0, 1, 3, 5, 6, 8, 11, 15, 18, 24, 26, 32, 34, 35, 39], "optmiz": [1, 8, 13, 32, 39], "oral": 31, "orang": 0, "order": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 15, 19, 21, 24, 25, 26, 28, 31, 32, 33, 35, 36, 37, 38, 39], "ordinari": [0, 2, 3, 7, 11, 13, 17, 18, 23, 35, 36, 37], "oreilli": [30, 31], "org": [0, 3, 4, 16, 20, 21, 23, 24, 25, 26, 30, 31, 32, 33, 34, 38], "organ": [6, 7, 10, 24, 35, 36], "orgin": 38, "orient": [1, 5, 28, 32, 33], "origin": [0, 3, 5, 6, 8, 11, 12, 13, 15, 24, 31, 32, 33, 34, 35, 36, 37], "orthogn": [5, 32, 33], "orthogon": [0, 5, 6, 8, 11, 13, 24, 31, 32, 33], "orthonorm": [5, 32, 33], "os": [29, 31], "oscar": [1, 39], "oscil": [3, 13, 34], "oskar": 31, "oskarlei": 31, "osl": 18, "oslo": [0, 23, 25, 26, 27, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "osx": [0, 23, 25, 31], "other": [0, 1, 2, 3, 5, 6, 7, 8, 10, 13, 14, 16, 19, 21, 22, 23, 27, 28, 29, 30, 32, 33, 34, 35, 36], "otherwis": [0, 1, 4, 7, 13, 24, 26, 31, 34, 36, 37, 39], "ouput": [5, 7, 12, 35, 36], "our": [1, 2, 3, 6, 7, 8, 9, 10, 12, 14, 15, 16, 17, 18, 19, 21, 23, 24, 28, 34, 35, 38], "ourmodel": 0, "ourselv": [0, 5, 6, 8, 11, 13, 31, 32, 33, 35], "out": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 15, 16, 21, 22, 23, 24, 25, 26, 28, 31, 32, 34, 35, 36, 37, 38, 39], "out_deriv": 39, "out_fil": 9, "outcom": [0, 7, 9, 10, 12, 28, 32, 36, 37], "outdoor": 9, "outer": [6, 12, 13], "outfil": 4, "outlier": [0, 8, 31, 32, 34], "outlin": [6, 10, 11, 35, 36], "outlook": 9, "outperform": [10, 34], "output": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 19, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37], "output_bia": [1, 39], "output_bias_gradi": [1, 38, 39], "output_func": 39, "output_nod": 39, "output_shap": 4, "output_weight": [1, 39], "output_weights_gradi": [1, 38, 39], "outputlayer1": [12, 37], "outputlayer2": [12, 37], "outsid": [4, 22], "over": [0, 1, 3, 4, 5, 6, 9, 10, 12, 13, 15, 16, 19, 22, 24, 25, 31, 32, 33, 34, 35, 36], "over1": 13, "overal": [1, 10, 34, 39], "overcast": 9, "overcom": [12, 13, 37, 38], "overdetermin": [0, 31], "overfit": [0, 1, 3, 6, 9, 10, 13, 26, 34, 35, 36, 39], "overflow": [5, 34, 35], "overflowerror": 39, "overhead": [12, 38, 39], "overlap": [3, 7, 8, 9, 37], "overleaf": [20, 25, 26], "overlin": [0, 5, 6, 9, 10, 11, 14, 24, 31, 32, 34], "overshoot": 34, "overst": 0, "overtrain": 4, "overview": [3, 20], "overwritten": 39, "own": [4, 5, 6, 8, 12, 13, 16, 18, 22, 23, 24, 33, 34, 35, 38, 39], "owner": [], "ownmsepredict": 0, "ownmsetrain": 0, "ownridgebeta": 32, "ownridgetheta": [0, 6, 32, 33, 34], "ownypredictridg": 0, "ownytilderidg": 0, "ox": [], "oxid": [], "p": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 24, 28, 31, 32, 33, 34, 35, 36, 37, 39], "p0": 2, "p1": 2, "p_": [2, 4, 8, 9], "p_hidden": 2, "p_i": [5, 28], "p_j": 28, "p_n": 28, "p_output": 2, "p_x": 28, "pa": 38, "pack": [0, 31], "packag": [0, 1, 3, 4, 5, 8, 11, 13, 15, 20, 22, 23, 25, 26, 28, 32, 33, 34, 39], "packtpub": 31, "packtpublish": 31, "pad": [3, 4], "page": [0, 23, 25, 26, 31, 33, 34, 35, 36], "pai": [0, 1, 9, 13, 15, 34, 39], "pair": [0, 2, 3, 9, 23, 28, 31], "paltform": 15, "panda": [0, 4, 5, 6, 7, 9, 11, 23, 25, 33, 34, 35, 36, 37], "pandoc": [], "panel": 31, "paper": [1, 34], "paper_fil": 34, "paradigm": [0, 31], "paragraph": 20, "parallel": [10, 13, 23, 24, 31], "param": 2, "paramat": 2, "paramet": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 16, 17, 18, 19, 21, 22, 25, 26, 28, 33, 34, 35], "parameter": [0, 6, 10, 31, 32], "parametr": [0, 6, 31, 32, 35, 36], "paramt": [3, 5, 35, 38], "parent": 38, "parser": 26, "part": [0, 1, 3, 5, 6, 10, 17, 19, 20, 21, 22, 24, 27, 28, 29, 31, 32, 35], "partial": [0, 1, 5, 6, 7, 8, 10, 11, 12, 13, 16, 21, 28, 31, 32, 33, 34, 36, 37, 38, 39], "particip": [15, 23, 27, 29, 31], "particl": [0, 4, 13, 28, 31], "particular": [0, 1, 2, 3, 5, 6, 9, 10, 11, 12, 13, 16, 25, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "particularli": [5, 6, 8, 11, 13, 28, 32, 33, 34, 35, 36], "partit": [1, 4, 9, 39], "partli": [6, 31], "partner": [15, 25, 26], "pass": [2, 3, 12, 14, 21, 34, 38], "password": [25, 26], "past": [10, 28, 34], "patch": [6, 28, 35], "path": [0, 4, 6, 7, 9, 23, 31, 34, 35, 36], "pathcollect": 17, "patholog": [], "patient": [7, 36, 37], "patter": 4, "pattern": [0, 3, 4, 12, 30, 31, 34, 37, 38], "paul": [], "pauli": [0, 31], "pav": [], "pc": [11, 15, 23], "pca": [0, 7, 23, 31, 32, 37], "pd": [0, 4, 5, 6, 7, 9, 11, 31, 32, 33, 34, 35, 36, 37], "pde": 2, "pdf": [0, 3, 4, 5, 6, 9, 15, 16, 19, 20, 25, 26, 30, 31, 35], "pedagog": [0, 31, 32], "penal": [6, 18, 32, 34], "penalti": [6, 13, 18, 25, 32, 34], "penros": [5, 6], "pentagon": [13, 33], "peopl": [1, 9, 13, 23, 25, 26, 34, 39], "per": [0, 1, 6, 21, 27, 29, 31, 34, 35, 36, 37, 39], "perc_print": 39, "percentag": [10, 11, 29, 39], "perceptron": [0, 1, 7, 31, 36], "peregrin": 31, "perez": [], "perfect": [0, 1, 13, 31, 34, 39], "perfectli": [4, 6, 35, 36], "perform": [0, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 14, 16, 18, 19, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38], "performac": 4, "perhap": [0, 5, 13, 31, 32, 33, 34], "perimet": 1, "period": [1, 4, 28, 39], "permiss": 15, "permit": [], "permut": 11, "persist": 13, "person": [5, 6, 7, 16, 20, 27, 29, 31, 32, 36], "perspect": 30, "pertin": [12, 26, 31, 38, 39], "petal": [8, 9], "peter": [30, 32], "petersen": [38, 39], "phantom": 28, "phase": [6, 12, 37, 38], "phenomena": 28, "phenomenon": 34, "phi": 8, "phi_k": 8, "philipp": [38, 39], "philosophi": 13, "phone": [29, 31], "photo": [4, 31], "php": [25, 26], "phrase": [0, 31], "physic": [0, 1, 4, 7, 12, 13, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "pi": [2, 3, 5, 6, 7, 9, 12, 13, 28, 35, 36, 37, 39], "pick": [1, 9, 10, 11, 13, 14, 25, 26, 34, 39], "pickl": 1, "pictur": [0, 31], "pie": [23, 31], "piec": [11, 14, 21], "pierr": [], "pillow": [0, 23, 25, 31], "pinv": [5, 6, 13, 25, 32, 33, 34, 37], "pip": [0, 1, 15, 23, 25, 31, 39], "pip3": [0, 1, 25, 31, 39], "pipelin": [0, 6, 8, 10, 32, 35, 36], "pippin": 31, "pit": 4, "pitfal": [6, 32], "pitt": [12, 37, 38], "pixel": [1, 3, 4, 26, 31, 39], "pixel_height": [1, 3, 39], "pixel_width": [1, 3, 39], "pkg_resourc": [], "pkgutil": [], "place": [0, 4, 6, 8, 13, 15, 24, 25, 31, 33, 35], "plai": [0, 3, 4, 5, 6, 8, 11, 18, 22, 23, 25, 31, 32, 33, 35, 36, 38, 39], "plain": [8, 10, 12, 13, 14, 25, 26, 33, 34, 38, 39], "plan": [6, 9, 29, 30, 31, 39], "plane": [8, 9], "plateau": [5, 33, 34], "platform": [23, 31], "plausibl": [12, 37, 39], "pleas": [13, 25, 26, 29, 31], "plenti": [1, 39], "plethora": [3, 12, 37, 38], "pliahhy2ibx9hdharr6b7xevztgzra1p": [37, 38, 39], "plot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 19, 20, 21, 23, 24, 25, 26, 28, 31, 32, 33, 34, 37, 39], "plot_all_sc": [25, 32], "plot_confusion_matrix": [7, 10, 37], "plot_count": 6, "plot_cumulative_gain": [7, 10, 37], "plot_data": 1, "plot_dataset": 8, "plot_decision_boundari": [9, 10], "plot_import": 10, "plot_iris_dataset": 21, "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, 37], "plot_surfac": [2, 6, 13], "plot_train": 9, "plot_tre": [9, 10], "plqvvvaa0qudcjd5baw2dxe6of2tius3v3": [37, 38, 39], "plt": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 39], "plu": [0, 3, 5, 7, 18, 31, 32, 36], "plugin": [], "pm": [8, 35], "pmatrix": 2, "pml": 30, "pn": 3, "png": [0, 4, 6, 7, 9, 31, 35, 36], "point": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 19, 20, 24, 25, 28, 29, 31, 32, 33, 34, 35, 36, 37, 39], "point_1": 4, "point_2": 4, "poisson": [23, 28, 31], "poli": [6, 8, 35, 36], "poly100_kernel_svm_clf": 8, "poly3": 0, "poly3_plot": 0, "poly_degre": 39, "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, 32, 35, 36], "polygon": [13, 33], "polym": [12, 37, 38], "polymi": 25, "polynomi": [0, 5, 6, 7, 8, 9, 10, 11, 15, 17, 19, 20, 25, 26, 31, 32, 34, 35, 36, 37, 38], "polynomial_featur": [6, 15, 16, 17, 35, 36], "polynomial_svm_clf": 8, "polynomialfeatur": [0, 6, 8, 9, 15, 16, 19, 32, 35, 36], "polytrop": [0, 6, 35, 36], "pool": 3, "pool_siz": 3, "poor": [1, 13, 33, 34, 39], "poorli": [0, 32], "popul": [0, 5, 31, 32], "popular": [0, 1, 3, 6, 7, 8, 9, 11, 12, 15, 23, 24, 25, 28, 32, 36, 37, 39], "popularli": [0, 31], "portabl": 10, "portion": [11, 13, 34], "pose": [0, 4, 5, 6, 11, 28, 31, 35], "posit": [0, 1, 2, 3, 5, 7, 8, 10, 11, 13, 14, 21, 24, 28, 31, 32, 33, 34, 36, 37, 39], "possibl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 21, 23, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "possibli": [6, 8, 13, 25], "post": [], "posterior": 5, "postpon": [0, 32], "postscript": [25, 26], "postul": 5, "potenti": [0, 3, 5, 6, 12, 13, 32, 34, 35, 37, 38], "pott": [12, 37, 38], "power": [0, 1, 5, 6, 8, 9, 12, 13, 31, 32, 33, 34, 35, 36, 37, 38, 39], "pp": [5, 6, 19, 35, 38, 39], "practic": [0, 5, 6, 7, 8, 16, 18, 19, 21, 25, 26, 28, 32, 35, 36, 37], "practition": [0, 1, 3, 31, 34, 39], "pre": 31, "preambl": [], "precalcul": 38, "preced": [1, 11, 12, 28, 37, 39], "preceed": [4, 39], "preceq": 8, "precis": [0, 2, 5, 11, 13, 24, 25, 26, 28, 31, 32, 34, 35, 38], "pred": [6, 35, 36, 37], "pred_train": 39, "pred_val": 39, "predicit": 0, "prediciton": 39, "predict": [0, 1, 5, 6, 7, 8, 9, 10, 15, 16, 17, 19, 22, 23, 25, 26, 30, 31, 32, 33, 34, 35, 36, 37, 39], "predict_prob": [1, 36, 37, 39], "predict_proba": [7, 10, 37], "predictedlabel": [36, 37], "predictor": [0, 5, 6, 7, 9, 10, 11, 31, 32, 34], "prefer": [0, 1, 6, 8, 9, 11, 13, 15, 20, 23, 25, 26, 31, 39], "prefil": [], "prepar": [0, 6, 24, 25, 26, 31, 32], "preprocess": [0, 4, 6, 7, 8, 9, 10, 11, 15, 16, 17, 18, 19, 25, 35, 36, 37, 39], "prerequisit": 0, "prescript": [25, 26], "presenc": 13, "present": [0, 5, 6, 7, 9, 12, 13, 24, 25, 26, 28, 31, 32, 33, 34, 37, 38, 39], "preserv": [3, 11, 24], "press": [13, 15, 30, 33, 38, 39], "pretrain": [1, 4, 39], "pretti": [0, 4, 8, 9, 21, 23, 25, 31], "prettier": [], "prev_centroid": 14, "prevent": [13, 28, 34], "previou": [0, 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 15, 16, 21, 22, 24, 25, 26, 28, 32, 33, 34, 37, 38, 39], "previous": [2, 3, 9, 10, 28], "price": [0, 4, 9, 13, 34], "primal": 8, "primari": [0, 7, 31, 36, 37], "prime": 28, "princip": [0, 5, 7, 23, 31, 32, 33, 37], "principl": [0, 6, 7, 8, 14, 31, 35, 36, 37], "print": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 18, 21, 22, 24, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "print_funct": [8, 9], "print_length": 39, "printout": [0, 31], "prior": [0, 5, 6, 31], "privat": 0, "pro": 26, "prob": [1, 28, 36, 37], "probabilist": [0, 30, 31, 32], "probabl": [0, 1, 3, 4, 6, 7, 10, 13, 21, 23, 31, 32, 34, 36, 37, 39], "problem": [0, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 23, 24, 25, 26, 28, 35], "probml": 30, "proce": [0, 5, 6, 7, 8, 9, 10, 11, 13, 24, 31, 32, 35, 38], "procedur": [2, 4, 5, 6, 8, 10, 11, 13, 32, 33, 34, 35, 36], "proceed": 24, "process": [0, 2, 4, 6, 9, 10, 12, 13, 23, 24, 25, 28, 30, 31, 33, 34, 35, 36, 37, 38], "procur": [], "prod": 30, "prod_": [1, 5, 7, 35, 36, 37, 39], "produc": [0, 3, 4, 5, 6, 9, 10, 11, 12, 13, 18, 20, 23, 24, 25, 26, 28, 31, 32, 35, 37, 38], "product": [0, 1, 3, 5, 6, 7, 8, 12, 13, 16, 17, 23, 24, 31, 32, 34, 35, 36, 37, 38, 39], "profess": [0, 31], "profit": [], "progag": 26, "program": [0, 1, 4, 5, 6, 8, 12, 14, 15, 23, 24, 27, 28, 29, 31, 32, 37, 39], "programm": 24, "progress": [1, 4, 14, 34, 36, 37, 39], "prohibit": [6, 35, 36], "project": [0, 1, 2, 3, 5, 11, 13, 15, 19, 22, 23, 27, 32, 33, 34, 35, 36, 37, 39], "project_root_dir": [0, 6, 7, 9, 31, 35, 36], "promin": [12, 37, 38], "promis": 8, "promot": [29, 31], "prompt": 20, "prone": [9, 15, 21, 38], "pronounc": [13, 23, 31, 34], "proof": [0, 11, 12, 13, 31, 33, 35, 36, 38], "prop": [34, 39], "prop_cycl": [], "propag": [2, 3, 13, 21, 22, 26, 34], "proper": [0, 2, 6, 7, 20, 35, 36], "properli": [1, 6, 8, 10, 13, 18, 20, 25, 26, 34, 39], "properti": [0, 1, 3, 12, 13, 16, 24, 31, 35, 37, 39], "propgag": 38, "proport": [0, 1, 5, 9, 11, 13, 28, 31, 32, 39], "propos": [1, 4, 6, 10, 25, 26, 31, 34, 39], "propto": [5, 13, 33, 34], "proton": [0, 31], "prove": [3, 13, 33, 34], "provid": [0, 1, 3, 4, 5, 6, 8, 9, 10, 12, 13, 20, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 38, 39], "proxi": [1, 13, 34, 39], "prune": 9, "pseudo": [24, 28, 34], "pseudocod": [25, 26], "pseudoinv": 5, "pseudoinvers": [5, 6, 25], "pseudorandom": [6, 28, 35], "psychologi": [0, 31], "pt": 13, "public": [0, 15, 23, 31], "publish": [38, 39], "pull": 15, "punish": [0, 1, 31, 39], "pure": [3, 9, 28], "purest": 9, "puriti": 9, "purpos": [0, 3, 10, 12, 14, 21, 31, 37, 38], "push": 15, "put": [1, 20, 25, 26, 34], "putmask": [], "py": 5, "pybtex": [], "pycod": 31, "pydata": 23, "pydevd_extension_api": [], "pydevd_plugin": [], "pydevd_plugin_plugin_nam": [], "pydot": 9, "pygment": [], "pyhton2": 31, "pylab": [7, 31, 36], "pypi": 23, "pyplot": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 39], "pythagora": 5, "python": [1, 2, 3, 5, 6, 8, 11, 12, 13, 14, 18, 20, 21, 22, 25, 26, 28, 32, 34, 38, 39], "python2": [0, 25], "python3": [0, 23, 25, 31], "pythonpath": [], "pytorch": [0, 23, 25, 26, 31, 38, 39], "pyzmq": [], "q": [5, 6, 8, 11, 28, 35, 39], "qp": 8, "qquad": [2, 11, 13, 24, 34], "qr": [5, 6, 24, 32, 33], "quad": [1, 13, 24, 39], "quadrat": [0, 8, 9, 13, 31], "qualit": [4, 9, 25, 26, 28], "qualiti": [0, 9, 23, 31, 32, 38], "quantifi": [1, 39], "quantil": 10, "quantit": [0, 6, 9, 25, 26, 31, 35, 36], "quantiti": [0, 2, 5, 6, 7, 9, 10, 11, 12, 14, 16, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "quantum": [4, 12, 30, 31, 37, 38], "quartil": [0, 32, 34], "quasi": 38, "quench": 5, "queri": 9, "question": [0, 5, 6, 9, 11, 12, 13, 25, 26, 29, 31, 32, 34, 35, 38, 39], "qugan": 4, "quick": [4, 28], "quicker": 34, "quickli": [1, 3, 9, 11, 13, 33, 34, 39], "quit": [1, 5, 6, 9, 10, 12, 15, 22, 32, 33, 35, 36, 37, 39], "quot": 4, "r": [0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 23, 24, 25, 28, 32, 33, 34, 35, 36, 37, 38, 39], "r2": [0, 5, 6, 19, 31, 32, 33], "r2_score": [0, 31], "r2score": [0, 31], "r_": 34, "r_0": 34, "r_1": 9, "r_2": 9, "r_j": 9, "r_m": 9, "r_t": 34, "rad": [], "rade": [], "radial": [8, 12, 37, 38], "radioact": 28, "radiu": [0, 1, 32, 34], "radziej": [], "ragan": [], "rain": 9, "rais": 39, "ram": 34, "ramanujam": [], "ramp": [1, 39], "ran0": 28, "ran1": 28, "ran2": 28, "ran3": 28, "rand": [0, 4, 5, 6, 9, 10, 13, 15, 19, 21, 22, 24, 31, 32, 33, 34, 35, 36, 39], "randint": [6, 9, 13, 34, 35], "randn": [0, 1, 2, 5, 6, 9, 11, 13, 15, 18, 21, 22, 31, 32, 33, 34, 35, 36, 37, 38, 39], "random": [0, 1, 2, 3, 4, 5, 6, 8, 9, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "random_forest_model": 10, "random_index": [13, 34], "random_indic": [1, 3, 39], "random_st": [7, 8, 9, 10, 11, 26, 36, 37], "randomforestclassifi": 10, "randomli": [1, 6, 9, 13, 14, 18, 33, 34, 35, 36, 39], "randomst": [36, 37], "rang": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 18, 19, 21, 22, 24, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "rangl": [0, 6, 11, 28, 31, 32], "rangle_x": 28, "rank": [5, 32, 33], "rankdir": 4, "raphson": [1, 8, 13, 39], "rapidli": [0, 34], "rare": [1, 13, 34, 39], "raschka": [26, 31, 32, 35, 36, 37], "rasckha": 31, "rashcka": [33, 34, 38, 39], "rashkca": [38, 39], "rate": [1, 2, 3, 4, 8, 9, 10, 12, 13, 18, 26, 33, 35, 36, 37, 38], "rather": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 24, 28, 31, 32, 33, 35, 36, 38, 39], "ratio": [4, 7, 9, 10, 11, 36, 37], "rational": [0, 31], "ravel": [5, 6, 7, 8, 9, 10, 11, 13, 24, 35, 36, 37, 39], "raw": [3, 34], "rbf": [8, 11, 12, 37, 38], "rbf_kernel_svm_clf": 8, "rbf_pca": 11, "rc": 28, "rcond": [0, 31, 32], "rcparam": [1, 3, 7, 8, 9, 10, 28, 31, 36, 39], "re": [2, 4, 13, 15, 33], "reach": [1, 4, 5, 6, 9, 10, 12, 13, 14, 33, 34, 35, 36, 38, 39], "react": [], "read": [0, 2, 3, 4, 5, 6, 7, 8, 11, 12, 16, 17, 19, 20, 24, 25, 26, 28, 30, 33], "read_csv": [0, 6, 7, 9, 35, 36], "read_fwf": [0, 31], "reader": [0, 6, 20, 24, 28, 31, 32, 34], "readi": [0, 1, 5, 6, 8, 10, 11, 12, 24, 31, 38, 39], "readili": [1, 39], "readm": [15, 20, 25, 26], "readthedoc": 23, "real": [0, 1, 4, 7, 10, 11, 12, 16, 18, 19, 24, 32, 35, 36, 37, 39], "real_loss": 4, "real_output": 4, "realist": [8, 31], "realiti": 28, "realiz": [1, 12, 37, 39], "realli": [0, 1, 31, 39], "rearrang": 13, "reason": [0, 1, 3, 4, 10, 13, 30, 31, 33, 34, 39], "reassign": 1, "reat": 39, "reber": 39, "recal": [5, 6, 9, 10, 11, 12, 22, 24, 28, 31, 32, 33, 34, 35, 36, 38, 39], "recarrai": [], "recast": 3, "receiv": [1, 3, 10, 12, 28, 37, 38, 39], "recent": [0, 6, 13, 30, 34, 35, 36, 38, 39], "recept": [3, 12, 37, 38], "receptive_field": 3, "recip": [0, 6, 7, 24, 25, 26, 31, 32, 36, 37], "reciproc": 5, "recogn": [0, 4, 5, 10, 31, 35], "recognit": [0, 1, 3, 12, 30, 31, 37, 38, 39], "recommen": 31, "recommend": [0, 2, 3, 4, 5, 6, 8, 13, 15, 19, 20, 21, 22, 23, 24, 25, 26, 30, 33, 34, 35, 36, 37, 38], "reconsid": 9, "reconstruct": 11, "record": [10, 25, 26, 27, 29, 31, 36, 37], "recreat": [15, 21], "rectangl": [9, 13, 33], "rectangular": [5, 32, 33], "rectifi": [1, 3, 12, 37, 39], "recur": [0, 23, 31], "recurr": [0, 1, 23, 31, 39], "recurs": [9, 23, 24, 31], "red": [0, 3, 4, 6, 8, 9, 34, 35], "redefin": [0, 10, 31, 32, 33], "redefinit": 33, "redistribut": [], "reduc": [1, 3, 5, 6, 9, 10, 11, 13, 21, 31, 33, 34, 35, 39], "reduct": [0, 10, 11, 23, 28, 31, 32], "reegress": 25, "ref": 20, "refer": [0, 1, 2, 3, 5, 6, 11, 12, 13, 14, 20, 24, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "referansestil": 20, "referenc": [2, 38, 39], "refin": [12, 37, 38], "refit": [6, 35, 36], "reflect": [0, 1, 4, 5, 25, 26, 28, 31, 39], "refresh": [23, 31], "refreshprogrammingskil": 31, "reg": [10, 11], "regard": [1, 9, 13, 39], "regardless": [12, 16, 37, 39], "regexp": [], "reggi": [], "regim": 34, "region": [3, 4, 6, 9, 12, 25, 34, 37, 38], "regist": [6, 28], "reglasso": [5, 33], "regr_1": [0, 9], "regr_2": [0, 9], "regr_3": [0, 9], "regress": [1, 8, 11, 12, 16, 20, 23, 24, 38, 39], "regressor": [0, 7, 10, 36, 39], "regret": [], "regridg": [0, 5, 6, 32, 33, 34], "regular": [0, 3, 4, 5, 6, 7, 9, 13, 17, 18, 26, 29, 31, 32, 33, 34, 35, 36, 37], "regularli": 15, "reilli": [0, 30, 31], "reinforc": [0, 8, 23, 31], "reiniti": 39, "reiter": 1, "reitz": [], "reject": 7, "rel": [0, 4, 6, 7, 9, 12, 13, 21, 28, 31, 32, 34, 35, 36, 37, 39], "relat": [0, 1, 3, 4, 5, 11, 13, 14, 19, 24, 28, 31, 32, 33, 35, 38, 39], "relationship": [0, 4, 9, 18, 31], "relativeerror": [0, 31, 32], "releas": [1, 23, 31, 39], "relev": [0, 1, 5, 7, 11, 23, 25, 26, 28, 31, 33, 34], "reli": [0, 6, 8, 34], "reliabilti": [25, 26], "reliabl": [7, 28, 36, 37], "relu": [3, 4, 21, 22, 26, 31], "relu_d": 22, "remain": [1, 2, 4, 6, 12, 24, 28, 32, 34, 35, 36, 37, 38, 39], "remaind": 28, "reman": 2, "remark": [1, 39], "rememb": [0, 8, 13, 20, 21, 22, 24, 25, 26, 31, 34], "remind": [0, 5, 11, 13, 19, 24, 28, 35], "remot": 15, "remov": [4, 5, 6, 18, 32, 33, 34], "renam": 15, "render": [0, 31, 32], "reorder": [5, 7, 32, 33, 36, 37], "reorgan": [0, 31], "repeat": [0, 1, 3, 4, 5, 6, 9, 10, 11, 13, 14, 24, 25, 28, 31, 32, 33, 34, 35, 36, 38, 39], "repeated": 31, "repeatedli": [0, 6, 10, 13, 35, 36], "repet": 3, "repetit": [6, 31, 32, 35, 36], "rephras": [13, 33], "replac": [0, 1, 3, 4, 5, 6, 10, 12, 14, 23, 25, 31, 32, 33, 35, 36, 38, 39], "replica": [6, 35], "repo": [15, 25, 26], "report": [31, 34, 36, 37], "repositori": [4, 20, 25, 26, 31], "reposotori": [], "repres": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "represent": [0, 1, 3, 6, 28, 31, 35, 36, 39], "representd": 3, "reproduc": [0, 5, 6, 9, 12, 15, 16, 18, 20, 23, 25, 26, 28, 31, 32, 38, 39], "repuls": [0, 31], "request": [0, 13, 34], "requir": [0, 1, 3, 4, 5, 6, 8, 9, 11, 12, 13, 15, 17, 18, 19, 20, 24, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "rerun": 39, "res1": 2, "res2": 2, "res3": 2, "res_analyt": 2, "res_analytical1": 2, "res_analytical2": 2, "res_analytical3": 2, "resaml": 6, "resampl": [0, 7, 10, 23, 31, 32, 39], "rescal": [0, 11, 12, 34, 37], "rescu": 5, "reseach": 6, "research": [0, 4, 13, 21, 22, 23, 26, 30, 31, 34], "resembl": [6, 28, 35], "reserv": [1, 5, 6, 28, 35, 36, 39], "reset": 39, "reset_weight": 39, "reshap": [0, 1, 2, 3, 4, 6, 8, 9, 10, 24, 31, 32, 35, 36, 39], "resid": 34, "residenti": [], "residu": [0, 5, 13, 31], "resiz": [5, 32, 33], "resnet": 34, "resort": 34, "resourc": [31, 34], "respect": [0, 1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 14, 16, 17, 18, 21, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "respond": [12, 37, 38], "respons": [0, 7, 9, 12, 31, 32, 36, 37, 38], "rest": [0, 5, 18, 21, 22, 32, 33, 34], "restat": [0, 12, 31], "restor": 4, "restored_discrimin": 4, "restored_gener": 4, "restrict": [0, 3, 9, 12, 31, 37, 38, 39], "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, 24, 25, 26, 28, 31, 34, 35, 36, 37], "retail": [], "retain": [5, 6, 32, 33, 34, 35, 36], "rethink": 35, "return": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 13, 14, 16, 17, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "return_data": 14, "return_sequ": 4, "return_x_i": 9, "reus": [1, 3, 6, 19, 20, 22, 25, 26, 38, 39], "reveal": [0, 12, 31, 37, 38], "revers": [1, 22, 24, 39], "review": [23, 24], "revis": [], "revisit": 14, "revolut": 31, "reward": [0, 4, 31], "rewrit": [0, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 19, 24, 25, 28, 33, 34, 36, 37, 38, 39], "rewritten": [2, 6, 8, 10, 28, 35], "rewrot": [13, 36, 37], "rf": 10, "rgb": 3, "rgoj5yh7evk": 23, "rh": [6, 35], "rho": [0, 10, 13, 34, 39], "rho2": 39, "rho_1": 10, "rho_2": 10, "rho_m": 10, "rich": [0, 31], "rid": [], "ride": 9, "rideclass": 9, "ridedata": 9, "ridg": [7, 11, 13, 20, 23, 26, 31, 35, 36, 37], "ridge_paramet": 17, "ridge_sk": 6, "ridgebeta": 33, "ridgetheta": 5, "right": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 19, 21, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "right_sid": 2, "rightarrow": [0, 1, 5, 6, 8, 11, 12, 13, 28, 31, 32, 33, 34, 35, 37, 38, 39], "rigor": [0, 31, 32, 33], "ring": 6, "rise": [0, 31], "risk": [0, 13, 31, 33, 34], "rival": 4, "river": [], "rlm": 31, "rm": [28, 34, 39], "rms_prop": 39, "rmse": [], "rmsporp": [13, 34], "rmsprop": [1, 3, 4, 13, 25, 26, 35, 38, 39], "rnd_clf": 10, "rng": [28, 36, 37], "rnn": [4, 12, 37, 38], "rnn1": 4, "rnn2": 4, "rnn_2layer": 4, "rnn_input": 4, "rnn_output": 4, "rnn_train": 4, "rntrick1": 28, "rntrick2": 28, "rntrick3": 28, "rntrick4": 28, "ro": [0, 13, 31, 33, 34], "robert": [19, 25, 30], "robust": [0, 31, 34], "robustscal": [0, 32, 34], "roc": [7, 10], "role": [0, 2, 5, 6, 8, 18, 23, 25, 31, 32, 33, 34, 35, 36, 38, 39], "roll": 6, "ronach": [], "room": [0, 29, 31], "root": [0, 5, 9, 13, 15, 28, 32, 33, 34, 38], "root_directori": [], "rot": 31, "rotat": [1, 8, 9, 10], "rotation_matrix": 9, "roughli": [1, 3, 18, 39], "round": [7, 9, 13, 37, 39], "routin": [13, 24, 31, 33], "row": [0, 1, 2, 5, 6, 9, 11, 16, 21, 24, 31, 32, 33, 35, 39], "rr": [5, 32, 33], "rrr": [5, 32, 33], "rubric": [], "rudg": [], "rug": [13, 33, 34], "rule": [0, 1, 5, 6, 13, 22, 25, 31, 32, 33, 37], "run": [0, 1, 2, 4, 5, 6, 8, 9, 11, 13, 15, 20, 21, 22, 23, 25, 26, 31, 32, 33, 34, 35, 36, 39], "rung": 26, "runtim": [1, 6, 14, 15, 39], "rust": [0, 23, 24, 31], "rvert": [1, 39], "rvert_2": [1, 39], "s41467": 26, "s_": [3, 6], "s_1": 6, "s_i": [6, 7, 36], "s_j": 6, "s_k": 6, "s_phenomenon": 25, "saddl": [13, 33, 34], "safeguard": [18, 34], "saga": 26, "sai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "said": [6, 9, 13, 33], "sake": [0, 5, 7, 11, 31, 32, 33, 36, 37, 38, 39], "sale": [0, 31], "sam": 31, "same": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 18, 20, 21, 22, 24, 25, 26, 28, 31, 32, 33, 37, 38, 39], "samm": 10, "sampl": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 14, 18, 19, 23, 24, 25, 28, 31, 32, 34, 35, 36, 37, 39], "sample_vari": 14, "sampleexptvari": 28, "samples_per_class": [36, 37], "samwis": 31, "sandbox": [], "sandboxmod": [21, 22], "sasha": [], "sastri": 11, "satisfactori": [0, 31], "satisfi": [1, 2, 3, 6, 8, 13, 24, 28, 33, 35, 39], "satur": [1, 6, 35, 36, 39], "save": [0, 4, 6, 7, 9, 13, 20, 22, 31, 34, 35, 36], "save_fig": [0, 6, 7, 9, 10, 31, 35, 36], "savefig": [0, 4, 6, 7, 9, 28, 31, 35, 36], "savetxt": 4, "saw": [5, 32], "scalabl": 10, "scalar": [2, 5, 6, 10, 32, 35, 38, 39], "scale": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 22, 23, 24, 25, 26, 29, 31, 33, 36, 37, 39], "scale_mean": 4, "scale_std": 4, "scaler": [0, 7, 8, 9, 10, 11, 17, 25, 32, 39], "scan": [5, 7, 36, 37], "scari": 5, "scatter": [0, 1, 6, 7, 8, 9, 14, 15, 17, 21, 31, 32, 34, 35, 36], "scenario": [6, 13, 33, 34], "schedul": [13, 34], "scheduler_arg": 39, "schedulers_bia": 39, "schedulers_weight": 39, "scheme": [1, 13, 33, 34, 36, 37, 39], "schrage": 28, "sch\u00f8yen": [6, 32, 34], "scienc": [0, 1, 10, 12, 13, 23, 27, 28, 29, 30, 33, 35, 36, 37, 38, 39], "scientif": [0, 20, 23, 25, 26, 31, 36, 37], "scientist": [0, 31], "scikit": [3, 5, 6, 8, 9, 10, 13, 15, 16, 20, 21, 23, 24, 25, 26, 30], "scikit_learn": [0, 37], "scikitlearn": 31, "scikitplot": [7, 10, 37], "scipi": [0, 3, 5, 6, 13, 23, 24, 25, 31, 32, 33, 35], "scl": 6, "scm": 15, "score": [0, 1, 3, 6, 7, 9, 10, 11, 15, 16, 19, 21, 25, 26, 29, 31, 32, 34, 35, 36, 37, 39], "scores_kfold": [6, 35, 36], "scratch": [1, 13, 16, 37, 38, 39], "script": [], "sdg": [13, 34], "sdv4f4s2sb8": [33, 34], "seaborn": [0, 1, 3, 6, 7, 26, 31, 37, 39], "seamless": [0, 23, 25, 31], "seamlessli": 39, "search": [0, 1, 3, 5, 9, 13, 15, 31, 33, 34, 39], "sebastian": [31, 38, 39], "sebastianraschka": [26, 31], "sec": 6, "second": [0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 14, 15, 16, 20, 21, 22, 23, 24, 28, 29, 31, 32, 33, 35, 36, 37, 38, 39], "second_correct": 39, "second_mo": 34, "second_term": 34, "secondari": 34, "secondeigvector": 11, "secondli": [12, 38, 39], "section": [4, 11, 16, 20, 24, 25, 28, 32, 34, 36], "sector": 0, "see": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 15, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "seed": [0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 13, 14, 18, 20, 21, 25, 26, 28, 31, 32, 33, 34, 35, 36, 38, 39], "seed_imag": 4, "seek": [1, 2, 8, 39], "seem": [1, 3, 4, 34, 39], "seemingli": [0, 31], "seen": [0, 1, 3, 5, 10, 12, 28, 39], "segment": [13, 33, 39], "seismic": 6, "seldomli": [0, 31], "select": [1, 5, 6, 8, 9, 10, 11, 15, 20, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 39], "selevet": 15, "self": [1, 5, 22, 32, 36, 37, 39], "sell": 4, "semest": [7, 27, 37], "semi": [8, 13, 33, 34], "semilogx": 6, "send": [5, 12, 13, 21, 22, 29, 31, 37, 38], "senior": [27, 29], "sens": [0, 4, 6, 8, 21, 31, 35], "sensibl": [3, 21], "sensit": [0, 5, 6, 9, 13, 31, 32, 34, 35, 36], "sent": [2, 21, 38, 39], "sentdex": [37, 38, 39], "sentenc": [4, 12, 37, 38], "separ": [0, 1, 2, 4, 6, 8, 9, 12, 14, 18, 21, 22, 23, 25, 28, 31, 34, 35, 37, 38, 39], "septemb": [18, 25, 31], "sequenc": [3, 4, 7, 9, 10, 12, 13, 23, 24, 28, 31, 33, 36, 37, 38], "sequenti": [1, 3, 4, 10, 12, 28, 37, 38, 39], "seri": [0, 1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 24, 31, 32, 33, 35, 37, 38, 39], "serif": [7, 28, 31, 36], "serv": [0, 1, 2, 3, 5, 7, 13, 26, 30, 31, 32, 33, 34, 36, 37, 39], "servic": [25, 26], "session": [1, 15, 20, 25, 26, 27, 29, 31], "set": [1, 4, 5, 6, 7, 8, 10, 11, 13, 14, 16, 17, 18, 21, 22, 23, 24, 25, 26, 28, 29, 34, 35, 36, 37], "set_major_formatt": 6, "set_major_loc": 6, "set_tick": [1, 8], "set_ticklabel": 1, "set_titl": [0, 1, 2, 3, 7, 12, 14, 31, 36, 37, 39], "set_xlabel": [0, 1, 2, 3, 7, 12, 31, 36, 37, 39], "set_xlim": [7, 12, 36, 37, 39], "set_xticklabel": 1, "set_ylabel": [0, 1, 2, 3, 7, 31, 37, 39], "set_ylim": [7, 12, 36, 37, 39], "set_ytick": [7, 37], "set_yticklabel": [1, 6], "set_zlim": 6, "seth": 4, "setminu": 6, "setosa": [8, 9], "setosa_or_versicolor": 8, "setp": [6, 35, 36], "setup": [1, 4, 6, 8, 22, 23, 26, 31, 32, 33, 38, 39], "sever": [0, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38], "sgd": [1, 3, 33, 39], "sgd_clf": 8, "sgdclassifi": 8, "sgdreg": 13, "sgdregressor": 13, "sgn": [5, 32, 33], "shall": [], "shallow": [13, 34], "shape": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 18, 21, 22, 24, 31, 32, 33, 34, 35, 36, 37, 38, 39], "share": [1, 3, 15, 31, 39], "share_mask": [], "shareabl": 15, "she": [7, 36, 37], "sheppard": [], "shibukawa": [], "shift": [1, 6, 12, 15, 18, 28, 32, 34, 37, 39], "ship": 3, "shire": 31, "short": [4, 5, 20, 25, 26, 39], "shortcom": [13, 33, 34], "shorten": 4, "shorter": 28, "shorthand": [31, 35], "shortli": [24, 31], "should": [0, 2, 3, 5, 6, 8, 9, 11, 12, 15, 18, 19, 20, 21, 22, 24, 25, 26, 28, 31, 32, 34, 35, 36, 38], "shouldn": [], "show": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "show_shap": 4, "shown": [0, 4, 5, 8, 12, 13, 24, 32, 33, 34, 37, 38, 39], "shrink": [3, 5, 6, 8, 11, 32, 33, 34], "shrinkag": [5, 6, 32, 33], "shrunk": 11, "shuffl": [0, 1, 4, 6, 13, 32, 34, 35, 36, 39], "sickit": [38, 39], "side": [0, 2, 5, 8, 12, 13, 24, 25, 26, 31, 33, 36, 37, 39], "sigh": [23, 31], "sigma": [0, 1, 5, 6, 7, 10, 11, 12, 13, 19, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "sigma0": 28, "sigma1": 28, "sigma2": 28, "sigma_": [5, 24, 31, 32, 33, 35], "sigma_0": [5, 32, 33], "sigma_1": [5, 32, 33, 38, 39], "sigma_2": [5, 32, 33, 38, 39], "sigma_fn": [7, 12, 36, 37, 39], "sigma_i": [0, 5, 31, 32, 33], "sigma_j": [5, 32, 33], "sigma_m": [6, 28, 35], "sigma_n": [11, 28], "sigma_t": 13, "sigma_x": 28, "sigmoid": [1, 2, 4, 7, 8, 10, 12, 21, 22, 26, 36, 37, 38], "sigmoid_autograd": 22, "sigmoid_d": 22, "sigmundson": [6, 32, 34], "sign": [1, 2, 7, 8, 10, 26, 28, 29, 36, 39], "signal": [1, 3, 10, 12, 34, 37, 38, 39], "signifi": 4, "signific": [1, 34, 39], "significantli": [1, 13, 18, 28, 33, 34, 39], "sim": [4, 5, 6, 13, 19, 28, 35], "similar": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14, 18, 23, 24, 25, 26, 31, 33, 35, 36, 37, 38, 39], "similarli": [0, 1, 3, 5, 8, 10, 13, 28, 31, 32, 33, 34, 38, 39], "similiar": 39, "simpl": [1, 2, 3, 5, 6, 7, 8, 10, 11, 12, 14, 16, 17, 22, 23, 24, 26, 28, 35, 37], "simple_plot": [], "simplefilt": 39, "simplepredict": 10, "simpler": [0, 1, 5, 6, 7, 13, 16, 23, 25, 26, 31, 33, 34, 39], "simplernn": 4, "simplest": [0, 1, 3, 4, 9, 10, 12, 14, 25, 31, 37, 38, 39], "simpletre": 10, "simpli": [0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 23, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "simplic": [2, 5, 6, 7, 8, 9, 10, 11, 12, 14, 32, 33, 34, 36, 37, 38, 39], "simplicti": [5, 32, 33], "simplif": 38, "simplifi": [0, 6, 9, 18, 22, 23, 25, 31, 32, 34, 35, 36, 38], "simplist": [3, 6, 28, 35], "simul": [6, 18, 34, 35, 36], "simultan": [6, 34, 35, 36], "sin": [0, 1, 2, 3, 4, 9, 12, 13, 24, 31, 37, 39], "sinc": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 13, 16, 18, 21, 22, 24, 25, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "sine": [3, 12, 37, 39], "singl": [0, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 18, 19, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 39], "singular": [0, 6, 13, 24, 31, 35], "sinusoid": 3, "site": [0, 25, 26, 27, 32], "situat": [0, 4, 5, 7, 13, 28, 31, 32, 33, 34, 36, 37], "six": [3, 28, 38], "size": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 18, 20, 21, 24, 25, 28, 31, 35, 36, 37, 38, 39], "sizesp": 34, "skeleton": 22, "sketch": 10, "ski": 9, "skill": 0, "skip": 11, "skl": [0, 6, 31, 32, 34], "sklearn": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 17, 19, 20, 21, 22, 26, 31, 32, 33, 34, 35, 36, 37, 39], "skplt": [7, 10, 37], "skrankefunct": 39, "sl": [6, 32, 34], "slack": 8, "slender": [], "slice": [2, 24, 31], "slide": [0, 3, 16, 25, 26, 28, 31, 32, 33, 38, 39], "slight": [6, 13, 35, 36], "slightli": [1, 2, 3, 5, 6, 7, 10, 28, 32, 33, 35, 36, 37, 38, 39], "slope": [8, 11, 12, 37], "slow": [0, 2, 8, 13, 18, 32, 33, 34], "slower": [5, 24, 31, 32, 33, 34], "slowest": 24, "slowli": [12, 34], "slp": [1, 39], "small": [0, 1, 2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 18, 21, 22, 23, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "smaller": [0, 1, 2, 5, 6, 8, 9, 11, 13, 21, 28, 31, 32, 33, 34, 35, 36, 39], "smallest": [0, 4, 14, 31], "smallest_row_index": 14, "smodin": [], "smooth": [0, 3, 6, 13, 25, 31, 33, 34], "smoother": 34, "sn": [0, 1, 3, 6, 7, 31, 37, 39], "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, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "soar": 6, "social": 0, "soft": [1, 7, 10, 12, 36, 37, 38, 39], "soften": 8, "softmax": [3, 7, 21, 22, 26, 36, 37], "softmax_vec": 21, "softwar": [0, 8, 23, 24, 38], "sokogskriv": 20, "sol": 8, "sol1": 21, "sole": [0, 6, 31], "solid": [0, 7, 36, 37], "solut": [0, 1, 2, 3, 5, 6, 8, 10, 11, 13, 18, 21, 24, 25, 26, 28, 31, 32, 33, 34, 35, 39], "solution_ev": 34, "soluton": 2, "solv": [0, 1, 3, 5, 6, 8, 10, 11, 12, 13, 16, 24, 25, 26, 31, 32, 38, 39], "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, 24, 26, 31, 37], "some": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 18, 19, 21, 22, 25, 26, 28, 31, 34, 35, 37, 39], "some_model": [6, 32, 34], "somehow": 4, "someon": 16, "someth": [0, 1, 3, 4, 7, 9, 11, 15, 19, 20, 25, 26, 28, 31, 32, 37, 39], "sometim": [0, 1, 11, 12, 13, 14, 19, 32, 34, 37, 38, 39], "somewhat": [26, 37], "soon": [24, 29, 32], "sophist": [0, 31], "sopt": 13, "sort": [5, 6, 9, 11, 28, 35, 36], "sound": [3, 5], "sourc": [0, 1, 3, 6, 23, 24, 25, 26, 28, 31, 34, 35, 36, 39], "source1": 22, "source2": 22, "space": [0, 1, 4, 5, 8, 9, 11, 12, 13, 14, 28, 32, 33, 34, 36, 37, 38, 39], "span": [0, 3, 5, 9, 11, 24, 31, 32, 33], "spare": [1, 39], "spars": [3, 6, 18, 24, 31, 34], "sparse_mtx": [24, 31], "sparsecategoricalcrossentropi": 3, "sparsiti": [10, 18], "spatial": [1, 2, 3, 12, 37, 38, 39], "speak": 28, "special": [6, 7, 10, 12, 13, 24, 28, 31, 32, 33, 34, 36, 37, 38, 39], "specif": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 15, 16, 23, 24, 25, 26, 28, 30, 31, 32, 33, 35, 36, 37, 38, 39], "specifi": [0, 3, 5, 6, 7, 9, 11, 13, 14, 28, 31, 33, 34, 35, 36, 37, 39], "specifici": [0, 10, 31], "spectacular": 3, "spectral": 1, "speech": [0, 1, 3, 4, 12, 37, 38, 39], "speed": [1, 2, 4, 13, 39], "spend": [16, 28, 34], "spent": [25, 26], "sphere": [0, 32, 34], "sphinx": [], "sphinx_book_them": [], "sphinxcontrib": [], "spike": 34, "spin": 6, "spite": 0, "spitzer": [], "spline": 8, "split": [1, 3, 4, 5, 6, 8, 9, 10, 11, 14, 16, 17, 20, 21, 22, 25, 26, 28, 31, 33, 34, 35, 36, 39], "splite": 0, "splitter": [1, 10], "spoiler": [], "spontan": 28, "spot": 3, "spread": [0, 11, 28, 31, 32, 36, 37], "spring": 39, "springer": [19, 25, 30, 31, 35, 36], "spuriou": [13, 34], "sqquar": 33, "sqrsignal": 3, "sqrt": [3, 4, 5, 6, 8, 10, 11, 13, 28, 32, 33, 34, 35, 38, 39], "squar": [1, 2, 3, 4, 7, 8, 9, 11, 13, 14, 15, 17, 18, 23, 24, 26, 28, 35, 36, 37, 38, 39], "squarederror": 10, "squaredeuclidean": 14, "squash": [12, 37, 39], "src": [], "srtm": 6, "srtm_data_norway_1": 6, "sso": 20, "stabil": [5, 25, 26, 34, 36, 37], "stabl": [0, 4, 5, 6, 9, 16, 20, 23, 25, 31, 32, 33, 34], "stack": [3, 4], "stage": [5, 13, 15, 25, 26, 34, 38, 39], "stagnat": 34, "stai": [0, 2, 4, 5, 11, 31, 32, 34, 39], "stand": [0, 5, 9, 12, 31, 32, 33, 37], "standard": [0, 1, 4, 5, 6, 7, 8, 10, 12, 17, 18, 19, 24, 25, 26, 28, 31, 33, 34, 36, 37, 38, 39], "standardscal": [0, 6, 7, 8, 9, 10, 11, 17, 32, 34], "standpoint": 34, "stanford": [13, 33], "start": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 21, 22, 24, 26, 28, 29, 31, 32, 33, 34, 35, 36, 38, 39], "start_tim": 14, "starter": [], "stat": [6, 35], "state": [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 23, 28, 31, 32, 33, 35, 36, 37, 38, 39], "statement": [0, 7, 24, 31, 37], "static": [], "stationari": [33, 34], "statist": [0, 1, 3, 4, 7, 9, 10, 11, 12, 13, 14, 19, 24, 25, 30, 32, 33, 34, 37, 38, 39], "statu": [0, 7, 15, 31, 36, 37], "stavang": 6, "stb": [], "std": [0, 4, 6, 18, 31, 32, 34, 35, 36], "stdout": 39, "steep": [13, 33, 34], "steepest": 34, "stefan": [], "step": [0, 1, 2, 4, 6, 7, 9, 10, 11, 12, 13, 14, 15, 18, 22, 24, 25, 31, 33, 37, 38, 39], "step_fn": [7, 12, 36, 37, 39], "step_length": [13, 34], "step_siz": 34, "steps_list": 9, "stereo": 3, "sticki": [], "still": [0, 2, 3, 5, 6, 11, 13, 21, 22, 26, 28, 32, 33, 34, 35, 36, 38], "stimuli": [12, 37, 38], "stk": [30, 31], "stk2100": [30, 31], "stk3155": [15, 25, 26, 27, 29], "stk4021": [30, 31], "stk4051": [30, 31], "stk4155": [27, 29], "stk5000": 30, "stochast": [0, 1, 5, 6, 8, 11, 12, 22, 26, 33, 35, 36, 38, 39], "stock": 4, "stoke": [12, 37, 38], "stone": [0, 7, 36, 37, 38], "stop": [1, 4, 9, 13, 14, 18, 33, 38, 39], "storag": [5, 32, 33], "store": [0, 1, 2, 3, 6, 11, 13, 22, 28, 31, 34, 39], "storehaug": [29, 31], "stori": [], "str": [1, 3, 4, 39], "straight": [0, 6, 8, 13, 31, 33, 35], "straightforward": [0, 2, 3, 5, 6, 8, 9, 10, 13, 24, 31, 32, 33, 35], "strategi": [0, 1, 9, 31, 39], "stratifi": [6, 35, 36], "stream": 34, "strength": [0, 5, 14, 32, 33], "stretch": 11, "strict": [8, 13, 33], "strictli": [8, 13, 33], "stride": [4, 24], "strike": 6, "string": [1, 39], "stroke": [7, 36, 37], "strong": [3, 6, 9, 10, 12, 24, 28, 34, 35, 37, 38], "strongli": [0, 8, 15, 20, 22, 23, 24, 26, 39], "stronli": [], "structur": [0, 1, 2, 3, 6, 9, 10, 12, 22, 23, 31, 35, 36, 37, 39], "stuck": [1, 13, 33, 34, 39], "student": [0, 15, 25, 26, 27, 29, 30, 31], "studi": [0, 3, 4, 5, 6, 7, 8, 11, 12, 13, 23, 25, 26, 30, 31, 32, 33, 34, 36, 38, 39], "studier": 30, "stuff": [21, 22], "style": [7, 9, 20, 24, 31], "stylesheet": [], "st\u00f8land": 29, "sub": [9, 12, 34, 37, 38], "subarrai": [], "subclass": [], "subdivid": [0, 24, 31], "subfield": 0, "subgradi": 34, "subject": [6, 8, 28], "sublicens": [], "sublinear": 34, "submit": 31, "subplot": [0, 1, 3, 4, 6, 7, 8, 9, 10, 14, 21, 31, 35, 36, 37, 39], "subplots_adjust": [8, 28], "subprogram": [24, 31], "subproject": [], "subract": [0, 32], "subroutin": [0, 31], "subscript": [1, 39], "subsequ": [1, 4, 5, 6, 12, 24, 28, 32, 33, 35, 37, 38], "subset": [1, 6, 9, 12, 13, 23, 31, 33, 34, 35, 36, 37, 38, 39], "subspac": [0, 8, 11, 32], "substanti": [9, 10, 34], "substep": 11, "substitut": [3, 6, 12, 16, 24, 35, 36, 37], "subsubset": 9, "subtask": 6, "subtl": [1, 39], "subtract": [0, 4, 5, 6, 11, 13, 18, 19, 24, 25, 28, 32, 34, 35, 36, 39], "subtre": 9, "succeed": [0, 4, 31], "success": [3, 7, 9, 13, 28, 36, 37], "successfulli": [4, 9], "succinctli": 34, "sudo": [0, 23, 25, 31], "suffer": [0, 1, 2, 5, 10, 31, 32, 33, 39], "suffici": [1, 6, 8, 11, 13, 33, 35, 36, 39], "suggest": [1, 13, 25, 26, 30, 33, 34, 39], "suit": [8, 12, 37, 38], "suitabl": [0, 15, 19, 28, 32, 34], "sum": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 19, 21, 24, 28, 31, 32, 33, 34, 37], "sum_": [0, 1, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "sum_i": [0, 2, 5, 6, 8, 13, 19, 25, 32, 33, 34, 35, 36], "sum_j": [6, 18, 34], "sum_ja_": 0, "sum_k": [6, 8, 12, 24, 38, 39], "sum_logist": 13, "sum_m": 3, "sum_n": 3, "sum_nx_": 3, "summar": [5, 6, 9, 26, 35, 36], "summari": [1, 3, 4, 10, 27, 33, 34, 39], "summat": [0, 3, 16, 32, 33], "sunni": 9, "super": [5, 32, 33, 34, 39], "superfici": 3, "superscript": [1, 12, 37, 38, 39], "supervis": [0, 5, 6, 7, 9, 12, 23, 31, 32, 33, 35, 36, 37, 38], "supplement": [7, 25, 26, 36, 37], "supplementari": 26, "suppli": [], "support": [0, 1, 9, 10, 11, 13, 20, 21, 23, 31, 32, 34, 36, 37, 38, 39], "suppos": [0, 5, 6, 7, 8, 10, 11, 12, 13, 24, 31, 32, 33, 34, 35, 36, 37, 38], "suppress": [5, 13, 33], "sure": [0, 1, 4, 6, 16, 20, 21, 22, 25, 39], "surf": 6, "surfac": [0, 6, 31, 34], "surpass": 6, "surpris": [0, 31], "surround": [3, 23], "survei": [0, 5, 6, 31, 32], "svc": [8, 9, 10], "svd": [0, 6, 11, 31, 35], "svdinv": 5, "svm": [8, 9, 10, 11], "svm_clf": [8, 10], "svn": [], "swap": 21, "swath": [5, 32, 33], "switch": [0, 39], "sy": [13, 33, 34, 39], "symbol": [1, 5, 11, 13, 23, 28, 31, 32, 33, 38, 39], "symmeteri": 1, "symmetr": [0, 5, 8, 11, 12, 13, 24, 31, 32, 37, 38], "symmetri": 6, "sympi": [0, 23, 25, 31, 38], "synonim": 28, "syntax": 13, "system": [0, 1, 3, 4, 6, 7, 9, 10, 12, 13, 15, 23, 24, 25, 31, 33, 34, 36, 37, 38, 39], "systemat": [4, 6, 35, 36], "t": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 28, 29, 31, 33, 34, 35, 36, 37, 38, 39], "t0": [3, 6, 13, 34], "t1": [2, 13, 34], "t2": 2, "t3": 2, "t9jjwsmsd1o": 35, "t_": 2, "t_0": [2, 9, 13, 34], "t_1": [13, 34], "t_b": 10, "t_batch": 39, "t_i": [1, 2, 5, 12, 26, 32, 33, 39], "t_j": 12, "t_k": 9, "t_test": 39, "t_train": 39, "t_val": 39, "tabl": [9, 25, 26, 28, 29, 31, 37], "tabul": [0, 31], "tabular": 31, "tackl": 4, "tag": [2, 3, 4, 5, 6, 7, 12, 13, 14, 24, 28, 32, 33, 36, 37, 38, 39], "tagrget": 38, "taht": [0, 31], "tail": 28, "tailor": [2, 8, 11, 31, 38], "taiwan": [0, 31], "take": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 19, 21, 22, 23, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "taken": [0, 1, 3, 6, 10, 13, 21, 24, 35, 39], "tan": 3, "tangent": [1, 4, 12, 13, 33, 37, 39], "tanh": [1, 4, 7, 8, 12, 36, 37, 39], "target": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15, 16, 18, 19, 21, 22, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "target_nam": [9, 21], "task": [0, 1, 3, 6, 9, 11, 12, 14, 21, 25, 31, 34, 35, 36, 37, 38, 39], "tau": [3, 5, 28], "taught": 31, "tax": [], "taylor": [2, 13, 33, 38], "taylornr": [13, 33], "tc": 8, "teach": [15, 27, 31, 35], "team": [1, 39], "teaser": 0, "technic": [0, 5, 6, 13, 25, 26, 33, 34, 35], "techniqu": [0, 1, 8, 10, 13, 23, 28, 30, 31, 32, 34, 35, 36, 39], "technologi": [0, 1, 39], "tell": [0, 4, 6, 10, 11, 13, 16, 28, 34, 35, 36], "temp": 1, "temp1": 1, "temp2": 1, "temperatur": [0, 9, 31], "templat": [18, 20], "temporari": [], "temporarili": [1, 39], "ten": [3, 31, 38], "tend": [3, 5, 6, 8, 9, 10, 12, 13, 14, 32, 34, 35, 36], "tendenc": [0, 31], "tension": [6, 35, 36], "tensor": 3, "tensorflow": [0, 2, 4, 8, 14, 23, 24, 25, 26, 30, 31, 32], "term": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 19, 22, 25, 26, 28, 31, 32, 33, 34, 36, 37], "term1": [5, 6, 11], "term2": [5, 6, 11], "term3": [5, 6, 11], "term4": [5, 6, 11], "termin": [0, 4, 5, 9, 10, 13, 15, 32, 33, 34], "terminarl": 15, "terrain": 6, "terrain1": 6, "test": [3, 4, 5, 6, 7, 8, 9, 10, 13, 16, 19, 20, 21, 24, 25, 28, 31, 33, 34, 35, 36, 37], "test_acc": 3, "test_accuraci": [1, 3, 39], "test_error": 6, "test_imag": [3, 4], "test_ind": [6, 35, 36], "test_input": 4, "test_label": [3, 4], "test_loss": 3, "test_pr": [1, 39], "test_predict": [1, 39], "test_rnn": 4, "test_scor": [7, 10, 37], "test_siz": [0, 1, 3, 5, 6, 10, 15, 17, 26, 32, 33, 34, 35, 36, 39], "test_split": 9, "testerror": [0, 6, 32, 35, 36], "testi": 4, "testpredict": 4, "testx": 4, "tex": [], "text": [0, 1, 2, 4, 5, 8, 9, 11, 13, 15, 18, 20, 24, 25, 26, 28, 30, 32, 33, 34, 35, 36, 39], "textbf": [], "textbook": [16, 25, 26, 32, 33, 35, 36], "textual": 9, "textur": 1, "tf": [1, 3, 4, 13, 14, 33, 39], "th": [0, 1, 2, 5, 6, 7, 9, 12, 13, 14, 24, 25, 28, 31, 32, 34, 35, 36, 37, 38, 39], "than": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 17, 21, 23, 28, 31, 32, 34, 35, 36, 37, 38, 39], "thank": [4, 6, 32, 34], "thats": 39, "theano": [1, 23, 31, 39], "thei": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 18, 20, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "them": [0, 1, 3, 4, 6, 8, 9, 10, 11, 12, 13, 18, 21, 24, 25, 26, 31, 32, 37, 38, 39], "theme": [0, 15, 31], "themselv": [0, 25, 26, 28, 31, 34], "thenc": [6, 35, 36], "theorem": [2, 6, 7, 32, 33, 36, 37, 39], "theoret": [0, 4, 10], "theori": [0, 1, 3, 8, 9, 12, 13, 19, 23, 25, 30, 31, 34, 37, 38, 39], "thereaft": [0, 5, 6, 11, 12, 24, 25, 31, 35, 36, 38, 39], "therebi": [0, 5, 7, 11, 25, 31, 32, 33, 36, 37, 38], "therefor": [0, 1, 2, 3, 4, 6, 7, 8, 11, 13, 19, 28, 31, 32, 33, 34, 35, 36, 37, 39], "therein": 11, "thereof": [0, 6, 13, 31, 34, 35], "theta": [0, 1, 4, 5, 6, 7, 13, 16, 25, 28, 31, 32, 33, 34, 36, 37, 38, 39], "theta1": 34, "theta2": 34, "theta_": [0, 1, 6, 7, 13, 31, 32, 33, 34, 36, 37, 39], "theta_0": [0, 5, 6, 7, 16, 31, 32, 33, 34, 36, 37], "theta_0x_": [0, 31, 32], "theta_1": [0, 5, 6, 7, 31, 32, 33, 34, 36, 37], "theta_1x_": [0, 31, 32], "theta_1x_0": [0, 31], "theta_1x_1": [0, 7, 31, 36, 37], "theta_1x_2": [0, 31], "theta_1x_i": [7, 32, 33, 34, 36, 37], "theta_2": [0, 31, 32], "theta_2x_": [0, 31, 32], "theta_2x_0": [0, 31], "theta_2x_1": [0, 31], "theta_2x_2": [0, 7, 31, 36, 37], "theta_2x_i": 32, "theta_3x_i": 32, "theta_4x_i": 32, "theta_closed_form": 18, "theta_closed_formol": 18, "theta_closed_formridg": 18, "theta_gdol": 18, "theta_gdridg": 18, "theta_i": [0, 1, 5, 31, 32, 33, 39], "theta_j": [0, 5, 6, 18, 31, 32, 34], "theta_k": [33, 34], "theta_linreg": [13, 33, 34], "theta_ol": 18, "theta_p": [7, 36, 37], "theta_px_p": [7, 36, 37], "theta_ridg": 18, "theta_t": [13, 34], "theta_tru": 18, "thetaand": 37, "thetaith": 34, "thetaor": 37, "thetavalu": 5, "thetaxor": 37, "thi": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 23, 24, 25, 26, 27, 28, 30, 32, 33, 34, 35, 36, 37, 39], "thing": [0, 1, 2, 4, 5, 7, 9, 15, 16, 18, 21, 22, 28, 31, 35, 37, 39], "think": [0, 1, 3, 4, 6, 9, 12, 13, 14, 28, 31, 32, 33, 34, 35, 37, 39], "third": [0, 3, 6, 13, 29, 31, 33, 34], "thirti": [7, 37], "thorughout": 31, "those": [0, 3, 5, 6, 8, 9, 10, 11, 24, 25, 26, 31, 32, 33, 34, 35, 36, 38], "though": [1, 2, 3, 4, 13, 16, 17, 19, 21, 22, 24, 28, 34, 39], "thought": [6, 14, 25, 26, 28, 35, 36], "thousand": [0, 1, 25, 32, 34, 39], "three": [0, 1, 3, 5, 6, 8, 9, 12, 21, 24, 25, 26, 27, 28, 29, 31, 32, 33, 35, 36, 37], "threshold": [1, 3, 9, 10, 11, 12, 13, 34, 36, 37, 38, 39], "through": [0, 1, 2, 3, 4, 5, 6, 8, 11, 12, 13, 14, 15, 21, 22, 23, 24, 25, 28, 31, 32, 33, 34, 35, 37, 39], "throughout": [0, 4, 5, 14, 15, 23, 24, 28, 31, 39], "throw": [3, 6, 28, 35], "thu": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "thumb": [0, 6, 25, 32], "thursdai": [], "tibshirani": [6, 19, 25, 30, 31, 35, 36], "tick_param": 6, "ticker": [6, 13, 28, 33, 34], "tif": 6, "tight_layout": [1, 7, 37], "tightli": 11, "tild": [0, 5, 6, 7, 11, 19, 25, 28, 31, 32, 33, 34, 35, 36, 38, 39], "till": [0, 4, 7, 8, 9, 10, 12, 24, 31, 32, 36, 37, 38, 39], "time": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 35, 36, 37, 38, 39], "timeit": 4, "timer": 4, "timeseri": [], "tini": [1, 34, 39], "tip": 3, "titl": [0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 13, 15, 20, 21, 28, 31, 33, 34, 35, 36, 39], "tm": [], "tmp": 13, "tn": [2, 3, 7], "to_categor": [1, 3, 4, 39], "to_categorical_numpi": [1, 39], "to_numer": [0, 6, 31, 35, 36], "todai": 3, "togeth": [0, 3, 6, 8, 11, 13, 22, 23, 31], "toi": 14, "token": [], "told": 13, "toler": [2, 14], "tolist": 4, "tomographi": [12, 37, 38], "too": [0, 2, 4, 5, 6, 9, 11, 13, 17, 18, 28, 30, 32, 33, 34, 35, 36], "took": [8, 31], "tool": [0, 1, 3, 6, 13, 15, 23, 32, 35, 36, 39], "toolbox": 8, "top": [0, 3, 5, 6, 9, 10, 19, 23, 31, 35], "topic": [0, 5, 6, 7, 8, 23, 25, 26, 32, 33, 35, 36, 37, 38], "topolog": [3, 12, 37, 38], "topologi": [1, 12, 39], "torkjellsdatt": [29, 31], "tort": [], "toss": [10, 28], "total": [0, 1, 2, 3, 4, 6, 7, 8, 10, 11, 12, 13, 14, 24, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "total_loss": 4, "totalclustervari": 14, "totalscatt": 14, "toward": [1, 2, 7, 12, 13, 15, 33, 36, 37, 39], "towardsdatasci": 34, "town": [], "tp": [4, 7], "tpng": 9, "tpu": [13, 23, 31], "tqdm": 6, "tr": [], "track": [3, 13, 14, 15, 22, 24, 32, 33, 34], "tract": [], "tractabl": [0, 31, 32], "trade": [5, 9, 20, 26, 34, 35], "tradeoff": [0, 5, 19, 25, 31, 32, 33], "tradit": [0, 1, 4, 6, 31, 35, 36, 39], "train": [2, 3, 5, 6, 8, 9, 10, 11, 12, 13, 16, 17, 20, 25, 26, 33, 34, 35, 36, 37], "train_acc": 39, "train_accuraci": [0, 1, 3, 31, 39], "train_dataset": 4, "train_end": [0, 1, 32, 39], "train_error": [6, 39], "train_imag": [3, 4], "train_ind": [6, 35, 36], "train_label": [3, 4], "train_network": 21, "train_pr": [1, 39], "train_siz": [0, 1, 3, 32, 39], "train_step": 4, "train_test_split": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 26, 31, 32, 33, 34, 35, 36, 37, 39], "train_test_split_numpi": [0, 1, 32, 39], "trainable_vari": 4, "trained_model": [6, 32, 34], "trainerror": [0, 32], "traini": 4, "training_checkpoint": 4, "training_dataset": 4, "training_gradi": [13, 34], "trainingerror": [6, 35, 36], "trainpredict": 4, "trainscor": 4, "trainx": 4, "trait": [0, 31], "trajectori": [4, 34], "transfer": [9, 31], "transform": [0, 5, 6, 7, 8, 9, 10, 11, 12, 13, 17, 21, 23, 24, 31, 32, 33, 34, 35, 36, 37, 38, 39], "transit": [6, 12, 37, 38], "translat": [1, 4, 6, 10, 31, 32, 34, 39], "transpos": [1, 5, 11, 21, 24, 32, 33, 39], "travers": [0, 5], "travi": [], "treat": [0, 1, 3, 6, 12, 13, 18, 21, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "tree": [0, 1, 23, 31, 39], "tree_clf": [9, 10], "tree_clf_": 9, "tree_clf_sr": 9, "tree_reg": 9, "tree_reg1": 9, "tree_reg2": 9, "trend": 28, "treue": 7, "trevor": [19, 25, 30], "tri": [2, 3, 4, 9, 13, 16, 34], "triain": 0, "trial": [0, 2, 4, 6, 13, 28, 31, 33, 34, 35, 36], "triangl": [13, 33], "triangular": 24, "trick": [3, 4, 8, 11, 13, 28, 34], "tricki": 22, "trickier": 28, "tridiagon": 24, "trillion": 23, "trim": [], "trivial": [0, 1, 5, 11, 28, 31, 33, 39], "troffa": [], "troubl": [0, 8, 12, 15, 21, 22, 32, 34, 38, 39], "truck": 3, "true": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 16, 17, 18, 19, 21, 22, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 39], "true_beta": 32, "true_fun": [6, 35, 36], "true_theta": [6, 34], "truelabel": [36, 37], "truli": 31, "truncat": 38, "try": [0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 18, 21, 22, 23, 24, 25, 26, 28, 31, 32, 33, 34, 36, 37, 38, 39], "tr\u00f6ger": [], "tucker": 8, "tuesdai": [29, 31, 36], "tumor": [7, 9, 36, 37], "tumour": [7, 37], "tunabl": 1, "tune": [4, 9, 13, 24, 31, 34], "tupl": [21, 39], "turn": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 24, 25, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "tutori": [1, 4, 39], "tv": 2, "tveito": 2, "tvw1zdmznwm": 37, "tweak": [1, 4, 10, 28, 39], "twice": [13, 33], "twist": 11, "two": [0, 1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 15, 17, 21, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35], "tx": [13, 33, 34, 37], "tx_1": [13, 33], "txt": [4, 15, 20, 25, 26], "ty": [13, 33], "type": [0, 1, 3, 6, 8, 10, 13, 21, 24, 28, 32, 33, 34, 35, 39], "typeset": 20, "typic": [0, 1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 20, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "typo": [25, 26], "u": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 21, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "u_": 24, "u_i": [12, 37], "u_m": 10, "ua": [0, 31], "ubuntu": [0, 23, 25, 31], "uci": [25, 26], "ufunc": [], "uio": [15, 20, 21, 25, 26, 29, 30], "uk": [], "un": 14, "unabl": [15, 21], "unari": [24, 31], "unbalanc": [6, 9, 35, 36], "unbias": [0, 5, 6, 31, 35], "uncent": [6, 32, 34], "uncertainti": [0, 5, 31], "uncertitud": 28, "unchang": [1, 3, 39], "uncom": [], "uncorrel": [10, 28], "undefin": [5, 32, 33], "under": [0, 1, 5, 6, 10, 13, 23, 25, 31, 32, 33, 34, 35, 39], "underdetermin": [0, 31], "underfit": [1, 6, 35, 36, 39], "underflowproblem": [5, 35], "undergo": [5, 21], "undergradu": [27, 29], "underli": [0, 1, 9, 13, 18, 28, 31, 34, 39], "underlin": [], "underscor": [], "underset": [4, 14], "understand": [0, 1, 3, 5, 6, 10, 13, 14, 15, 19, 20, 21, 23, 31, 32, 33, 34, 38, 39], "understood": [8, 13], "underwai": [], "undesir": 8, "undetermin": [5, 8, 35], "undo": 4, "unexpect": [6, 35], "unexpected": 28, "unexplain": 18, "unfair": [6, 32], "unfortun": [1, 8, 9, 10, 39], "unicode_liter": [8, 9], "uniform": [0, 1, 5, 6, 11, 13, 25, 28, 31, 33, 34, 36, 37, 39], "uniformli": [13, 28, 33, 34], "unifrompdf": 28, "unimport": [13, 33], "union": [5, 6, 35, 36], "uniqu": [0, 2, 6, 13, 14, 24, 31, 35, 36, 37], "unique_class": [36, 37], "unique_cluster_label": 14, "unit": [0, 1, 3, 4, 5, 10, 12, 18, 28, 31, 32, 33, 34, 37, 38, 39], "unitari": [5, 6, 24, 32, 33], "unitarili": [24, 31], "uniti": 28, "univari": 28, "univers": [0, 1, 2, 13, 23, 25, 26, 27, 29, 31, 32, 33, 34, 35, 36, 37, 39], "unix": [1, 39], "unknow": [0, 24, 31], "unknown": [0, 1, 3, 4, 5, 6, 8, 10, 13, 19, 24, 25, 31, 32, 33, 34, 35, 36, 38, 39], "unknowwn": 12, "unlabel": [1, 39], "unless": [0, 3, 6, 11, 13, 25, 26, 31, 33, 35, 38], "unlik": [1, 3, 8, 13, 33, 34, 39], "unnecessarili": 9, "unord": 3, "unpickl": [], "unpleas": [], "unpublish": 34, "unravel": [1, 39], "unrol": [3, 11], "unscal": 19, "unseen": [0, 7, 9, 15, 36, 37], "unstabl": [1, 39], "unsupervis": [0, 1, 4, 12, 23, 31, 37, 38, 39], "unsymmetr": [24, 31], "until": [1, 2, 4, 9, 12, 13, 14, 21, 33, 34, 37, 39], "untouch": 0, "unusu": [12, 37, 38], "up": [1, 3, 4, 5, 6, 8, 10, 11, 13, 14, 16, 18, 19, 20, 21, 22, 23, 24, 25, 28, 29, 34, 37], "updat": [1, 2, 10, 12, 13, 14, 15, 18, 19, 21, 22, 26, 35, 36, 37], "update_chang": 39, "update_matrix": 39, "update_weight": 22, "uploa": 31, "upload": [15, 20, 23, 25, 26, 30], "upon": [0, 1, 6, 7, 11, 24, 38, 39], "upper": [0, 8, 9, 16, 24, 32], "uppercas": [24, 31], "upsampl": 4, "upscal": 4, "uptad": 38, "upward": [], "url": [31, 32, 37], "us": [4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 17, 20, 21, 24, 28, 30, 35], "usag": [0, 8, 23, 31, 32, 38], "usd": [], "usd10000": [], "use_bia": 4, "usecol": [0, 31], "useless": [1, 39], "user": [0, 1, 2, 4, 6, 7, 15, 23, 24, 25, 31, 32, 36, 37, 39], "usernam": [15, 25, 26], "usetex": 28, "usg": 6, "usr": 28, "usual": [0, 3, 4, 7, 12, 13, 14, 31, 34, 36, 37, 38], "ut": 5, "utf": [], "util": [1, 3, 4, 6, 7, 10, 14, 19, 31, 35, 36, 39], "ux": 24, "v": [2, 4, 5, 6, 11, 13, 15, 23, 32, 33, 35, 36, 37, 38, 39], "v0": 28, "v1": 28, "v2": 28, "v5": [], "v8xr": [37, 38, 39], "v_": 34, "v_0": [11, 34], "v_t": 34, "va": 1, "vahid": 31, "val": 13, "val_acc": 39, "val_accuraci": 3, "val_error": 39, "val_loss": 4, "val_set": 39, "vale": 2, "valid": [0, 1, 4, 7, 9, 10, 13, 23, 28, 31, 32, 34, 37, 39], "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, 24, 25, 26, 31, 34, 37, 38, 39], "valuat": 9, "valued_at_a": 39, "valued_at_z": 39, "valueerror": [], "valy": 4, "van": [0, 19, 25, 31, 32, 33, 34], "vandenbergh": [8, 13, 33], "vandermond": [0, 31], "vanilla": [0, 6, 11, 14, 32, 34], "vanish": [1, 4, 13, 28, 33, 38], "var": [5, 6, 10, 11, 19, 25, 28, 32, 35, 36], "var_x": 28, "varabl": 8, "varepsilon": [5, 6, 19, 35], "varepsilon_": [5, 6, 35], "varepsilon_i": [5, 6, 35], "vari": [0, 1, 3, 5, 6, 10, 21, 31, 35, 36, 38, 39], "variabl": [0, 1, 2, 5, 6, 7, 8, 10, 11, 12, 13, 14, 21, 24, 31, 32, 34, 35, 36, 37, 38, 39], "varianc": [0, 1, 5, 7, 9, 10, 11, 13, 14, 18, 20, 23, 24, 26, 28, 31, 32, 33, 34, 37, 39], "variance_i": [5, 11, 32], "variance_x": [5, 11, 32], "variant": [0, 1, 6, 8, 12, 13, 26, 31, 32, 33, 34, 37, 38, 39], "variat": [3, 4, 11, 31], "varieti": [0, 3, 12, 23, 25, 31, 37, 38], "variou": [1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 16, 19, 20, 23, 24, 25, 28, 31, 32, 33, 34, 37, 38, 39], "varydimens": 4, "vast": 34, "vastli": 3, "vaue": 1, "vault": 0, "vdot": [2, 13, 33, 34], "ve": [25, 26, 34], "vec": [6, 35], "vector": [0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 13, 14, 17, 18, 21, 22, 23, 33, 34, 35, 36, 38, 39], "vector_mean": 14, "ventur": [0, 8, 23, 31], "venv": 15, "verbos": [1, 3, 4, 36, 37, 39], "veri": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 21, 22, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 39], "verifi": [3, 11, 24, 31], "versatil": [8, 31], "versicolor": [8, 9], "version": [0, 3, 10, 13, 14, 15, 21, 22, 23, 24, 25, 26, 28, 31], "versu": [1, 34, 39], "vert": [0, 1, 5, 6, 7, 8, 9, 11, 13, 16, 17, 31, 32, 33, 34, 35, 36, 37, 38, 39], "vert_1": [5, 6, 32, 33, 34], "vert_2": [5, 6, 11, 17, 32, 33, 34, 35], "vi": 39, "via": [0, 5, 6, 7, 8, 9, 10, 11, 12, 19, 23, 24, 25, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "vidal": 11, "video": [0, 1, 12, 23, 27, 29, 31, 32, 33], "view": [1, 3, 5, 6, 12, 13, 28, 30, 31, 33, 34, 35, 37, 39], "vii": 39, "viii": 39, "violat": 8, "virginica": 9, "viridi": [0, 1, 2, 3, 31, 39], "virtanen": [], "virtual": [1, 34, 39], "viscos": 13, "viscou": 13, "visibl": 15, "vision": [0, 3], "visit": 34, "visual": [0, 3, 11, 12, 18, 23, 31, 32, 37, 38], "visualis": 1, "visualstudio": [15, 16, 19], "viz": [6, 8, 28], "vmap": 13, "vmax": [1, 6], "vmh0zpt0tli": 34, "vmin": [1, 6], "voic": 3, "volatil": 34, "volum": [0, 3, 31], "von": [38, 39], "vote": [10, 31], "voting_clf": 10, "votingclassifi": 10, "votingsimpl": 10, "vscode": [21, 22], "vstack": [5, 11, 24, 28, 31, 32, 36, 37, 39], "vt": [5, 32, 33], "w": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 21, 22, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "w1": [8, 21, 22], "w2": [8, 11, 21, 22], "w3": 8, "w_": [1, 12, 37, 38, 39], "w_0": 38, "w_1": [8, 24, 38, 39], "w_1a_0": [38, 39], "w_1x": [38, 39], "w_1x_": 8, "w_1x_1": 8, "w_2": [8, 24, 38, 39], "w_2a_1": [38, 39], "w_2x_": 8, "w_2x_2": 8, "w_3": 24, "w_4": 24, "w_g": [21, 22], "w_hidden": 2, "w_i": [1, 2, 10, 38, 39], "w_ix_i": [12, 37, 38], "w_j": 24, "w_m": 24, "w_output": 2, "w_px_": 8, "w_px_p": 8, "w_t": [], "wa": [1, 3, 4, 5, 6, 7, 10, 11, 12, 14, 17, 19, 21, 24, 31, 32, 34, 35, 36, 37, 38, 39], "wai": [0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 18, 19, 21, 22, 24, 28, 31, 32, 33, 34, 37, 39], "walk": 9, "walker": 28, "wall": 34, "walt": [], "wang": [0, 31], "want": [0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 20, 21, 22, 23, 25, 26, 28, 31, 32, 33, 34, 35, 36, 38, 39], "warn": [4, 39], "warrant": [6, 35, 36], "warranti": [], "wast": [3, 34], "watch": [23, 33, 34, 35, 37, 38, 39], "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, 24, 25, 26, 28, 29, 30, 32, 33, 35, 36, 37], "weak": [9, 10, 14], "weaker": 34, "weather": [1, 12, 37, 38, 39], "web": [23, 27, 29, 31], "weblink": 26, "webpag": 31, "websit": [6, 24, 25, 26, 27, 31], "wedg": [8, 28, 38, 39], "wednesdai": [29, 31, 36], "wee": 11, "week": [0, 5, 6, 7, 25, 26, 27, 29], "week41": 26, "week42": 26, "weekli": [15, 16, 23, 25, 27, 29, 30, 31, 37], "weierstrass": 38, "weight": [1, 2, 3, 6, 7, 9, 10, 12, 13, 18, 21, 22, 26, 28, 34, 36, 37, 38], "weight_arrai": 39, "weigth": [2, 22], "welchlab": [37, 38, 39], "welcom": [8, 15, 23], "well": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 13, 15, 16, 20, 21, 22, 23, 24, 25, 26, 28, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39], "went": 8, "were": [0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, 28, 31, 34, 35, 36, 37, 38, 39], "wessel": [0, 19, 25, 31, 32, 33, 34], "wg_nf1awssi": 38, "what": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 25, 26, 28, 34, 37, 38, 39], "whatev": [3, 21], "when": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 21, 22, 24, 25, 26, 28, 31, 32, 33, 35, 36, 37, 38, 39], "whenev": [13, 15, 28, 34, 38], "where": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 26, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39], "wherea": [6, 28, 34, 35, 36], "wherefrom": [25, 26], "wherein": [1, 12, 37, 38, 39], "whether": [0, 3, 5, 7, 9, 25, 26, 28, 31, 36, 37], "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, 27, 28, 29, 31, 32, 33, 35, 36, 37, 38], "whichev": [1, 3, 39], "while": [0, 1, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 19, 20, 21, 22, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "white": 9, "whiteboad": 34, "whiteboard": [32, 33, 34, 35, 36, 37, 38, 39], "who": [0, 15], "whole": [1, 3, 4, 5, 9, 11, 13, 21, 34, 39], "whom": [], "whose": [0, 6, 10, 26, 28, 32, 35, 36], "whow": [11, 32], "why": [0, 1, 3, 6, 13, 15, 16, 17, 19, 21, 25, 32, 33, 39], "wide": [0, 1, 3, 6, 7, 12, 23, 24, 25, 31, 35, 36, 37, 38, 39], "widehat": [6, 35], "width": [0, 3, 8, 9, 21, 31], "wieringen": [0, 19, 25, 31, 32, 33, 34], "wiki": 25, "wikipedia": 25, "win": [10, 34], "wind": 9, "window": [], "wing": [29, 31], "winther": 2, "wiothout": 6, "wiscons": 7, "wisconsin": [10, 37, 39], "wisdom": [6, 32, 34], "wise": [1, 5, 12, 13, 21, 32, 33, 34, 37, 39], "wish": [0, 2, 5, 7, 8, 11, 13, 14, 18, 24, 25, 26, 31, 32, 33, 34, 36, 37, 38, 39], "with_std": [0, 32], "wither": 6, "within": [0, 2, 3, 4, 7, 9, 12, 13, 14, 28, 30, 31, 33, 36, 37], "withinclust": 14, "without": [0, 1, 5, 6, 8, 9, 11, 12, 13, 15, 18, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "wo5dmep_bbi": [37, 38, 39], "won": [0, 15, 31, 38], "wonder": 8, "word": [0, 1, 3, 4, 5, 6, 7, 14, 19, 25, 26, 28, 31, 32, 33, 34, 39], "work": [0, 1, 4, 6, 7, 8, 9, 13, 15, 16, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 31, 32, 34, 35, 36, 37, 38, 39], "workabl": 34, "workaround": [], "workhors": 34, "workload": 34, "workshop": 31, "world": [0, 8, 16, 32], "worldwid": [0, 31], "worri": 15, "wors": [0, 1, 3, 4, 6, 31, 34, 35, 36, 39], "worth": [9, 19, 21], "worthi": [25, 26], "would": [0, 1, 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 18, 20, 22, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "wouldn": [], "wrap": [6, 24, 31], "wrapper": [21, 22], "write": [0, 1, 2, 3, 5, 6, 7, 8, 12, 13, 15, 16, 18, 21, 24, 31, 32, 34, 35, 36, 37, 38], "writer": [36, 37], "writerow": [36, 37], "written": [0, 2, 3, 5, 11, 12, 13, 16, 23, 24, 25, 26, 28, 31, 32, 33, 34, 38, 39], "wrong": [1, 8, 15, 19, 39], "wrongli": 10, "wrote": [5, 11, 32], "wrt": [10, 13, 21, 22, 34, 38, 39], "wth": [10, 13, 34], "wurstemberg": [38, 39], "www": [20, 23, 24, 25, 26, 30, 31, 33, 34, 35, 37, 38, 39], "wx_1": 8, "x": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 24, 25, 26, 28, 31, 33, 34, 35, 36, 37, 38, 39], "x0": [8, 36, 37], "x1": [4, 8, 9, 10, 13, 36, 37], "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, 24, 28, 31, 32, 33, 34, 35, 36, 38], "x_0": [0, 5, 11, 18, 24, 31, 32, 35, 38], "x_1": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 18, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "x_2": [0, 2, 5, 6, 7, 8, 9, 10, 11, 13, 24, 28, 31, 32, 33, 35, 36, 37, 38, 39], "x_3": [8, 24, 28, 38], "x_4": [24, 38], "x_5": 38, "x_6": 18, "x_batch": 39, "x_bin": [36, 37], "x_center": 11, "x_data": [1, 39], "x_data_ful": [1, 39], "x_hidden": 2, "x_i": [0, 1, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 24, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "x_input": 2, "x_ix_": [0, 31], "x_iy_i": 8, "x_j": [0, 2, 8, 9, 12, 16, 28, 32, 34, 37, 38], "x_jy_j": 8, "x_k": [12, 14, 24, 28, 32, 37], "x_l": [28, 38], "x_m": [6, 12, 24, 28, 35, 37], "x_mean": [18, 34], "x_multi": [36, 37], "x_n": [0, 2, 3, 6, 8, 11, 12, 13, 24, 28, 31, 33, 35, 37, 38], "x_new": [9, 10], "x_norm": [18, 34], "x_offset": [6, 32, 34], "x_output": 2, "x_p": [3, 7, 9, 36, 37], "x_poli": 9, "x_poly10": 9, "x_pred": 4, "x_prev": 2, "x_reduc": 11, "x_sampl": [], "x_scale": 8, "x_small": 13, "x_std": [18, 34], "x_t": 34, "x_test": [0, 1, 3, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 26, 32, 33, 34, 35, 36, 37, 39], "x_test_": 17, "x_test_own": 6, "x_test_scal": [0, 6, 7, 9, 10, 11, 32, 34], "x_tot": 4, "x_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 26, 31, 32, 33, 34, 35, 36, 37, 39], "x_train_": 17, "x_train_mean": [6, 32, 34], "x_train_own": 6, "x_train_r": 19, "x_train_scal": [0, 6, 7, 9, 10, 11, 32, 34], "x_val": [1, 39], "xarrai": [23, 31], "xavier": [1, 39], "xbnew": [13, 33, 34], "xcode": [0, 23, 25, 31], "xdclassiffierconfus": 10, "xdclassiffierroc": 10, "xg_clf": 10, "xgb": 10, "xgbclassifi": 10, "xgboost": 9, "xgboot": 10, "xgbregressor": 10, "xgparam": 10, "xgtree": 10, "xi": [8, 13, 34, 36, 37], "xi_": 8, "xi_1": 8, "xi_i": 8, "xinv": 37, "xk": 8, "xla": [13, 23, 31], "xlabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 21, 28, 31, 32, 33, 34, 35, 36], "xlim": [6, 10, 35, 36], "xm": 9, "xmesh": 13, "xnew": [0, 13, 31, 33, 34], "xp": 28, "xpanda": [0, 32], "xpd": [5, 11, 32], "xplot": 0, "xscale": [0, 32], "xsr": 9, "xt_x": [13, 33, 34], "xtest": [6, 35, 36], "xtick": [3, 6, 8, 9, 35, 36], "xtrain": [6, 35, 36], "xu": [0, 31], "xx": [0, 24, 31], "xy": [0, 6, 8, 24, 31], "xytext": 8, "xyz": [], "xz": [24, 31], "y": [0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "y1": 4, "y2": 4, "y3": 4, "y_": [0, 1, 5, 6, 10, 11, 24, 31, 32, 35, 36, 39], "y_0": [0, 5, 11, 24, 31, 32, 35], "y_1": [0, 5, 8, 9, 11, 13, 24, 31, 32, 33, 34, 35], "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, 24, 31, 32], "y_2y_1": 8, "y_2y_1k": 8, "y_2y_2": 8, "y_2y_2k": 8, "y_3": [0, 9, 24], "y_4": 24, "y_bin": [36, 37], "y_binari": [36, 37], "y_center": [18, 34], "y_data": [0, 1, 5, 6, 31, 32, 33, 34, 39], "y_data_ful": [1, 39], "y_decis": 8, "y_fit": [0, 32], "y_i": [0, 1, 5, 6, 7, 8, 9, 10, 11, 12, 13, 19, 24, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "y_if_": 10, "y_indic": [36, 37], "y_ix_": [0, 31], "y_ix_i": [7, 8, 13, 32, 33, 34, 36, 37], "y_iy_jk": 8, "y_j": [6, 8, 12, 25, 35, 36, 37, 38, 39], "y_k": [12, 37], "y_m": 24, "y_mean": [18, 34], "y_model": [0, 4, 5, 6, 31, 32, 33, 34], "y_multi": [36, 37], "y_n": [8, 13, 33, 34], "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, 32, 34], "y_onehot": [36, 37], "y_plot": 9, "y_pred": [0, 1, 4, 6, 7, 8, 9, 10, 26, 32, 34, 35, 36, 37, 39], "y_pred1": 9, "y_pred2": 9, "y_pred_bin": [36, 37], "y_pred_multi": [36, 37], "y_pred_rf": 10, "y_pred_tre": 10, "y_prob": [36, 37], "y_prob_bin": [36, 37], "y_prob_multi": [36, 37], "y_proba": [7, 10, 37], "y_sampl": [], "y_scaler": [6, 32, 34], "y_test": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 26, 32, 33, 34, 35, 36, 37, 39], "y_test_onehot": [1, 39], "y_test_predict": [], "y_tot": 4, "y_train": [0, 1, 3, 4, 5, 6, 7, 9, 10, 11, 15, 16, 17, 19, 26, 31, 32, 33, 34, 35, 36, 37, 39], "y_train_mean": [6, 32, 34], "y_train_onehot": [1, 39], "y_train_predict": [], "y_train_r": 19, "y_train_scal": [6, 32, 34], "y_true": [36, 37], "y_val": 1, "yand": 37, "ye": [3, 6, 7, 35, 36, 37], "year": [0, 23, 31], "yet": [0, 1, 6, 8, 11, 13, 20, 21, 31, 36, 38, 39], "yi": [13, 34, 36, 37], "yield": [0, 2, 5, 6, 8, 10, 12, 13, 14, 24, 28, 31, 33, 34, 35, 37, 38, 39], "yk": 8, "ylabel": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 13, 21, 28, 31, 32, 33, 34, 35, 36], "ylim": [3, 6, 35, 36], "ym": 9, "ymesh": 13, "yn": 0, "yo": [8, 9, 10], "yor": 37, "yoshiki": [], "yoshua": [1, 30, 39], "you": [0, 1, 3, 4, 5, 6, 8, 9, 10, 11, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36, 38, 39], "young": 0, "your": [1, 2, 4, 5, 6, 8, 11, 13, 15, 17, 19, 20, 21, 22, 23, 24, 31, 33, 34, 35, 36, 37, 38, 39], "your_model_object": 16, "yourself": [11, 13, 31, 33], "youtu": [32, 33, 35, 37], "youtub": [23, 33, 34, 35, 37, 38, 39], "ypred": [6, 35, 36], "ypredict": [0, 13, 31, 32, 33, 34], "ypredict2": [13, 33, 34], "ypredictlasso": [5, 33], "ypredictol": [0, 5, 33], "ypredictown": [6, 32, 34], "ypredictownridg": [6, 32, 33, 34], "ypredictridg": [0, 5, 6, 32, 33, 34], "ypredictskl": [6, 32, 34], "ytest": [6, 35, 36], "ytick": [3, 6, 8, 9, 35, 36], "ytild": [0, 6, 31, 32, 35, 36], "ytildelasso": [5, 33], "ytildenp": [0, 31, 32], "ytildeol": [0, 5, 33], "ytildeownridg": [6, 32, 33, 34], "ytilderidg": [5, 6, 32, 33, 34], "ytrain": [6, 35, 36], "yuxi": 31, "yx": [24, 31], "yxor": [37, 39], "yy": [24, 31], "yz": [24, 31], "z": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 21, 22, 24, 28, 31, 32, 35, 36, 37, 38, 39], "z1": [21, 22], "z2": [21, 22], "z_": [1, 2, 12, 24, 31, 38, 39], "z_0": [24, 31, 38], "z_1": [24, 31, 38, 39], "z_2": [22, 24, 31, 38, 39], "z_c": [1, 39], "z_h": [1, 39], "z_hidden": 2, "z_i": [1, 12, 37, 39], "z_j": [1, 12], "z_k": [12, 32, 38, 39], "z_m": [1, 39], "z_matric": 39, "z_mod": 9, "z_o": [1, 39], "z_output": 2, "za": [], "zalando": 26, "zaman": 28, "zaxi": 6, "zero": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, 19, 21, 24, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "zeros_lik": [4, 36, 37], "zeroth": 32, "zfill": 4, "zip": [4, 6, 21, 22, 36, 37], "zm_h": [0, 31], "zn": [], "zone": [], "zoom": 31, "zscout": [], "zx": [24, 31], "zy": [24, 31], "zz": [24, 31], "\u00f8yvind": [6, 32, 34], "\u03b4": 39}, "titles": ["<span class=\"section-number\">3. </span>Linear Regression", "<span class=\"section-number\">14. </span>Building a Feed Forward Neural Network", "<span class=\"section-number\">15. </span>Solving Differential Equations with Deep Learning", "<span class=\"section-number\">16. </span>Convolutional Neural Networks", "<span class=\"section-number\">17. </span>Recurrent neural networks: Overarching view", "<span class=\"section-number\">4. </span>Ridge and Lasso Regression", "<span class=\"section-number\">5. </span>Resampling Methods", "<span class=\"section-number\">6. </span>Logistic Regression", "<span class=\"section-number\">8. </span>Support Vector Machines, overarching aims", "<span class=\"section-number\">9. </span>Decision trees, overarching aims", "<span class=\"section-number\">10. </span>Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods", "<span class=\"section-number\">11. </span>Basic ideas of the Principal Component Analysis (PCA)", "<span class=\"section-number\">13. </span>Neural networks", "<span class=\"section-number\">7. </span>Optimization, the central part of any Machine Learning algortithm", "<span class=\"section-number\">12. </span>Clustering and Unsupervised Learning", "Exercises week 34", "Exercises week 35", "Exercises week 36", "Exercises week 37", "Exercises week 38", "Exercises week 39", "Exercises week 41", "Exercises week 42", "Applied Data Analysis and Machine Learning", "<span class=\"section-number\">2. </span>Linear Algebra, Handling of Arrays and more Python Features", "Project 1 on Machine Learning, deadline October 6 (midnight), 2025", "Project 2 on Machine Learning, deadline November 10 (Midnight)", "Course setting", "<span class=\"section-number\">1. </span>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", "Week 38: Statistical analysis, bias-variance tradeoff and resampling methods", "Week 39: Resampling methods and logistic regression", "Week 40: Gradient descent methods (continued) and start Neural networks", "Week 41 Neural networks and constructing a neural network code", "Week 42 Constructing a Neural Network code with examples"], "titleterms": {"": [8, 10, 33, 34, 35, 36, 37], "0": 39, "04": [], "05": [], "06": [], "07": [], "1": [0, 15, 16, 17, 18, 19, 20, 21, 22, 25, 26, 32, 38, 39], "10": [26, 38], "11": [], "13": 39, "15": [19, 35], "19": 19, "1a": 18, "2": [0, 15, 16, 17, 18, 19, 20, 21, 22, 26, 31, 32, 33, 38, 39], "20": [], "2017": [], "2018": [], "2019": [], "2023": 29, "2025": [25, 36, 37, 38, 39], "22": 36, "26": 36, "27": [], "29": 37, "2a": [], "2b": [], "3": [0, 15, 16, 17, 18, 19, 20, 21, 22, 32, 38, 39], "34": [15, 31], "35": [16, 32], "36": [17, 33], "37": [18, 34], "38": [19, 35], "39": [20, 36], "3a": 18, "3b": 18, "4": [0, 15, 16, 17, 18, 19, 20, 21, 22, 32, 39], "40": 37, "41": [21, 38], "42": [22, 39], "4a": 18, "4b": 18, "5": [0, 16, 18, 19, 20, 21, 22], "6": [21, 22, 25, 38], "7": [21, 22], "8": [22, 34], "A": [0, 1, 4, 8, 9, 31, 35, 36, 37, 39], "AND": 37, "And": [31, 32, 34], "But": 34, "In": [29, 38], "Ising": 6, "OR": 37, "The": [0, 1, 2, 3, 5, 6, 7, 8, 9, 11, 12, 15, 23, 31, 32, 33, 34, 35, 36, 37, 38, 39], "To": 31, "With": [4, 33], "a11i": [], "about": [26, 31, 32, 33], "abov": [33, 38, 39], "abstract": 20, "accuraci": 34, "across": 34, "activ": [1, 12, 21, 26, 37, 38, 39], "ad": [0, 6, 20, 25, 31, 32, 37, 38, 39], "adaboost": 10, "adagrad": [13, 34], "adam": [13, 34], "adapt": [10, 34], "add": [], "adjust": [1, 39], "advanc": 25, "adversari": 4, "again": [3, 9], "against": 26, "ai": [25, 26, 31], "aim": [8, 9, 21, 22, 31], "aka": 31, "al": 34, "algebra": [24, 31], "algorithm": [9, 10, 11, 12, 26, 31, 32, 33, 34, 38, 39], "algortithm": [13, 33, 36, 37], "all": [8, 38, 39], "an": [0, 4, 10, 15, 20, 31, 38], "analys": [5, 32, 33], "analysi": [0, 5, 6, 11, 23, 25, 26, 28, 31, 32, 33, 35, 36, 38], "analyt": [0, 16, 18, 26], "analyz": [38, 39], "ani": [13, 22, 33, 36, 37], "anoth": [9, 33, 35, 36], "api": [], "appli": 23, "approach": [0, 8, 14, 31, 34, 35, 36], "approxim": [12, 38], "architectur": [1, 39], "arrai": [24, 31], "artifici": [37, 38], "assist": 29, "assumpt": 35, "august": [], "author": [], "autocorrel": 28, "autograd": [2, 13, 22, 34], "automat": [13, 34, 38], "avail": 20, "avali": [], "averag": 34, "b": [25, 26], "back": [1, 11, 12, 32, 33, 38, 39], "background": [23, 25, 26, 35], "backpropag": 22, "bag": 10, "base": [13, 34, 35], "basic": [0, 5, 7, 9, 10, 11, 24, 32, 33, 36, 37, 38], "batch": [1, 22, 34, 39], "bay": 5, "befor": 11, "bengio": 39, "beta": [], "better": [8, 37], "bia": [6, 19, 25, 34, 35, 36], "bias": [38, 39], "binari": [1, 39], "bind": 31, "bird": 10, "blind": [], "block": [], "boldsymbol": [18, 32, 35], "book": [19, 38, 39], "boost": 10, "bootstrap": [6, 10, 35, 36], "boston": [], "breast": 1, "brief": [31, 35, 36], "bring": [12, 38, 39], "browser": [], "bsd": [], "build": [1, 3, 9, 39], "c": [25, 26, 31], "calcul": [18, 32, 33], "can": [31, 34, 35, 36, 38], "cancer": [1, 7, 9, 11], "cart": 9, "case": [8, 10, 28, 32, 33, 34, 36, 37], "cdn": [], "cell": [], "central": [13, 23, 28, 33, 35, 36, 37], "chain": [12, 38, 39], "challeng": 34, "chang": 10, "changelog": [], "channel": 31, "chi": [0, 31], "choic": [17, 39], "choos": [1, 34, 39], "cifar01": 3, "citat": [], "class": [36, 37, 38], "classic": 11, "classif": [1, 9, 10, 26, 36, 37, 39], "classifi": [8, 36], "claus": [], "clip": [1, 39], "cluster": 14, "cnn": 3, "code": [1, 2, 5, 9, 11, 12, 13, 14, 15, 16, 20, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "collect": [1, 3, 39], "color": [], "colorblind": [], "combin": 34, "commun": 31, "compact": [36, 37, 38, 39], "compar": [2, 10, 16], "comparison": [33, 34], "compet": 34, "compil": [], "complet": [32, 38, 39], "complex": [0, 6, 25, 32], "complic": [6, 38], "compon": 11, "comput": [9, 19, 34], "computation": [35, 36], "computerlab": 31, "con": [9, 34], "concept": 28, "condit": 33, "confid": 35, "conjug": 13, "consider": [38, 39], "constraint": 34, "construct": [38, 39], "contain": [], "content": [], "continu": 37, "contn": 31, "contrast": [], "contributor": [], "converg": 34, "convex": [8, 13, 33, 34], "convolut": [3, 12, 37, 38], "copyright": [], "core": [], "correct": 34, "correl": [11, 32, 37], "correspond": [], "cost": [1, 10, 32, 33, 34, 35, 36, 37, 38, 39], "count": 38, "cours": [23, 27, 30, 31], "covari": [5, 11, 28, 32], "cover": 31, "creat": [16, 20], "creator": [], "critic": 26, "cross": [6, 25, 35, 36, 37], "custom": 21, "cython": 31, "d": [25, 26], "dark": [], "data": [0, 1, 3, 6, 7, 9, 11, 15, 17, 18, 21, 23, 28, 31, 32, 36, 37, 38, 39], "dataset": [1, 3, 18, 39], "david": 31, "deadlin": [25, 26, 31], "deadllin": 29, "decai": [2, 34], "decis": [9, 10], "decomposit": [5, 11, 24, 32, 33], "deeep": [], "deep": [1, 2, 31, 34, 36, 37, 38, 39], "defin": [1, 31, 38, 39], "definit": [19, 38, 39], "deflist": [], "degre": [0, 17, 32], "deliver": [15, 16, 19, 20, 25, 26], "deliveri": [25, 26], "delta": 35, "dens": 0, "depend": [], "depth": 26, "deriv": [5, 12, 16, 17, 19, 32, 33, 34, 35, 38, 39], "descent": [2, 10, 13, 18, 25, 33, 34, 37], "design": 32, "detail": [3, 31], "develop": [1, 39], "diagon": 11, "differ": [8, 26, 34], "differenti": [2, 13, 34, 38], "diffus": 2, "dimens": 34, "dimension": [2, 3, 8, 18], "direct": [], "disadvantag": 9, "discret": 28, "discrimin": 31, "discuss": 37, "distribut": [5, 28, 35], "do": [1, 34, 37, 39], "document": 20, "doe": [32, 33, 37], "domain": 28, "down": [1, 39], "dropout": [1, 39], "e": [25, 26], "each": [21, 36], "economi": [32, 33], "electron": [25, 26], "element": [0, 28, 31], "elimin": 24, "elu": 39, "empir": 34, "energi": 31, "ensembl": 10, "entri": [38, 39], "entropi": [9, 36, 37], "environ": [0, 15], "equat": [0, 2, 12, 32, 33, 36, 37, 38, 39], "error": [0, 10, 31, 32, 33, 35, 36], "essenti": 31, "estim": 35, "et": 34, "etc": 31, "euler": 2, "evalu": [1, 26, 38, 39], "evid": 34, "exampl": [1, 2, 3, 4, 6, 7, 8, 9, 10, 31, 32, 33, 34, 35, 36, 37, 38, 39], "exercis": [0, 6, 15, 16, 17, 18, 19, 20, 21, 22, 32, 38], "expect": [19, 28, 35], "expens": [35, 36], "experi": 28, "explicit": [38, 39], "explod": 39, "explor": 0, "exponenti": [2, 34], "express": [16, 17, 19, 32, 36, 37, 38, 39], "extend": [33, 36, 37, 38], "extrapol": 4, "extrem": [10, 31], "ey": 10, "f": [25, 26], "fall": 29, "famili": [1, 31, 39], "famou": 24, "fantast": [32, 33], "faq": [], "featur": [9, 16, 24, 32], "februari": [], "feed": [1, 12, 22, 37, 38, 39], "figur": 20, "file": [], "fill": [], "final": [12, 32, 34, 38, 39], "find": [16, 18, 35], "fine": [1, 39], "first": [4, 12, 31, 33, 38, 39], "fit": [0, 10, 15, 16, 31, 33], "fix": [32, 33, 34], "float": 38, "fold": [35, 36], "forc": 3, "forest": 10, "form": 18, "format": [25, 26, 31], "formula": 18, "forward": [1, 2, 12, 22, 37, 38, 39], "foster": 31, "fourier": 3, "frank": 6, "freedom": [0, 17, 32], "frequent": [32, 34], "frequentist": [0, 31], "from": [5, 10, 12, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "full": [2, 34, 39], "function": [0, 1, 6, 7, 8, 10, 11, 12, 13, 25, 26, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39], "funtion": 39, "further": [3, 5, 32, 33], "g": [25, 26], "gan": 4, "gate": [37, 39], "gaussian": 24, "gd": [13, 34], "gener": [4, 9, 31, 36, 37, 38], "geometr": [11, 33], "get": [20, 38], "gini": 9, "github": 15, "glorot": 39, "goal": [15, 16, 17, 18, 19, 20], "good": [0, 20, 31], "goodfellow": 34, "gotthard": [], "grade": [29, 31], "gradient": [1, 2, 10, 13, 18, 22, 25, 26, 33, 34, 37, 38, 39], "greativ": [], "group": 36, "growth": 2, "guid": [], "h": 25, "ha": 23, "hand": [22, 38, 39], "handl": [24, 31], "happen": [35, 36], "hessian": [32, 33, 34], "hidden": [2, 38, 39], "high": [], "histogram": 35, "histori": [], "homogen": 39, "hous": [], "how": 16, "hyperbol": [37, 39], "hyperparamet": [1, 17, 39], "hyperplan": 8, "i": [0, 1, 31, 39], "id3": 9, "idea": 11, "ideal": 33, "ident": 35, "identifi": 35, "ii": 31, "iid": 35, "illustr": [33, 37, 38], "implement": [1, 16, 17, 18, 39], "implic": [5, 32, 33], "import": [5, 24, 31, 32, 33, 38, 39], "improv": [1, 34, 39], "includ": [13, 25, 34, 36, 37, 38], "incorpor": [], "increment": 11, "independ": 35, "index": 9, "inform": 29, "ingredi": 38, "init": 39, "input": [2, 21, 22, 38, 39], "insight": 39, "instal": [23, 25, 31], "instructor": 29, "intermedi": 38, "interpret": [5, 11, 19, 31, 32, 33, 35], "interv": 35, "introduc": [11, 13, 32], "introduct": [0, 6, 20, 23, 24, 25, 26, 31, 37, 38], "invers": [5, 24], "invert": [32, 33], "ipython": [], "iter": 10, "its": 32, "j": [], "jacobian": 32, "januari": [], "jax": 13, "job": 37, "julia": 31, "jungl": 10, "jupyt": [], "k": [35, 36, 38, 39], "kera": [1, 3, 39], "kernel": [8, 11], "l": [38, 39], "lab": [33, 34, 35, 36, 37, 38, 39], "lagrangian": 8, "lasso": [5, 6, 25, 32, 33], "last": [32, 34, 37, 38, 39], "later": [5, 32, 33], "layer": [1, 2, 3, 12, 21, 22, 38, 39], "layout": [38, 39], "learn": [0, 1, 2, 11, 13, 14, 15, 16, 17, 18, 19, 20, 23, 25, 26, 31, 32, 33, 34, 35, 36, 37, 38, 39], "least": [5, 6, 16, 19, 25, 31, 32, 33, 34], "lectur": [31, 33, 34, 35, 36, 37, 38, 39], "level": 10, "librari": [23, 26, 31], "licens": [], "light": [], "likelihood": [7, 35, 36, 37], "limit": [1, 13, 28, 33, 34, 35, 39], "linear": [0, 8, 13, 15, 24, 31, 32, 33, 36], "link": [5, 11, 30, 32, 35], "list": [38, 39], "literatur": [25, 26], "logist": [7, 31, 36, 37, 39], "loss": [32, 33, 34], "lu": 24, "ma": [], "machin": [0, 8, 13, 23, 25, 26, 31, 33, 36, 37], "machineri": 26, "made": 35, "main": [28, 31], "make": [0, 9, 10, 20, 32], "mani": [10, 12], "markdown": [], "mask": [], "maskedarrai": [], "mass": 31, "materi": [25, 26, 31, 32, 33, 34, 35, 36, 38, 39], "math": [5, 32, 33], "mathemat": [3, 5, 8, 32, 33, 37, 38, 39], "matplotlib": [], "matric": [5, 24, 31], "matrix": [1, 5, 11, 12, 16, 24, 31, 32, 33, 34, 37, 39], "matter": 0, "max": 32, "maximum": [35, 36, 37], "me": [], "mean": [0, 32, 33, 36], "measur": 37, "meet": [5, 10, 28, 31, 32], "memori": 34, "mercer": 8, "metadata": [], "method": [6, 9, 10, 13, 25, 31, 33, 34, 35, 36, 37, 39], "metric": 19, "midnight": [25, 26], "min": 32, "mini": 34, "minibatch": 34, "minim": [31, 36, 37], "mit": [], "ml": 31, "mle": 35, "mlp": 12, "mnist": [3, 4], "mode": 38, "model": [0, 1, 4, 6, 12, 15, 17, 31, 37, 38, 39], "moment": 34, "momentum": [13, 25, 34], "mondai": [33, 34, 35, 37, 38], "moon": [8, 9], "more": [3, 6, 24, 25, 31, 32, 33, 34, 35, 36, 37, 38, 39], "motiv": 34, "move": 34, "multi": [37, 38, 39], "multiclass": 39, "multilay": [12, 37, 38], "multipl": [1, 3, 17, 21, 39], "multipli": 8, "multivari": 38, "myst": [], "ncsa": [], "need": [25, 31], "network": [1, 2, 3, 4, 7, 12, 26, 31, 34, 36, 37, 38, 39], "neural": [1, 2, 3, 4, 7, 12, 26, 31, 34, 37, 38, 39], "neuron": [37, 38], "new": [4, 18, 35, 38], "newton": [33, 34, 36, 37], "nn": [38, 39], "node": [38, 39], "noeds": 39, "non": [8, 34], "none": 34, "norm": 26, "normal": [0, 1, 35, 39], "notat": [12, 37], "note": [25, 26, 32, 33], "notebook": [], "novemb": 26, "now": [1, 9, 13, 33, 34, 35, 36], "nuclear": [0, 31], "nueral": 36, "numba": 31, "number": [0, 2, 22, 28, 32, 34, 38], "numer": [2, 25, 26, 28], "numpi": [24, 31], "object": [3, 22, 39], "observ": [38, 39], "obtain": 11, "octob": [25, 38, 39], "od": 2, "off": [6, 19, 25], "ol": [5, 6, 15, 16, 18, 25, 33, 35], "onc": 21, "one": [2, 12, 18, 22, 33, 38, 39], "ones": [37, 39], "open": [], "oper": [24, 38], "optim": [1, 8, 13, 18, 23, 31, 32, 33, 34, 36, 37, 38, 39], "option": [21, 22], "order": [13, 18, 34], "ordinari": [5, 6, 16, 19, 25, 31, 32, 33, 34], "organ": [0, 31], "orient": [22, 39], "oslo": 30, "other": [4, 9, 11, 12, 24, 25, 26, 31, 37, 38, 39], "ouput": [38, 39], "our": [0, 4, 5, 11, 13, 25, 26, 31, 32, 33, 36, 37, 39], "outcom": [23, 31], "output": [2, 38, 39], "over": [38, 39], "overarch": [0, 4, 8, 9, 21, 22, 31, 32, 38], "overview": [10, 31, 34], "own": [0, 10, 11, 25, 26, 31, 32], "packag": [24, 31], "panda": [31, 32], "paper": 39, "parallel": 38, "paramet": [31, 32, 36, 37, 38, 39], "paramt": 18, "part": [13, 23, 25, 26, 33, 36, 37, 38, 39], "partial": 2, "pass": [1, 22, 39], "pca": 11, "pdf": 28, "percepetron": [38, 39], "perceptron": [12, 37, 38, 39], "perform": [1, 9, 39], "period": 3, "perspect": [1, 39], "pitaya": [], "plan": [32, 33, 34, 35, 36, 38], "plethora": 31, "plot": [35, 36], "point": [4, 38], "poisson": 2, "polici": [], "polynomi": [3, 16, 18, 33], "popul": 2, "popular": 31, "practic": [13, 29, 31, 34], "pre": [1, 3, 39], "preambl": [25, 26], "predict": [4, 21], "predictor": [36, 37], "preprocess": [32, 34], "prerequisit": [3, 23, 31], "present": 20, "princip": 11, "principl": 3, "pro": [9, 34], "probabl": [5, 28, 35], "problem": [1, 2, 13, 31, 32, 33, 34, 36, 37, 38, 39], "procedur": [9, 31], "process": [1, 3, 21, 39], "program": [2, 13, 25, 26, 33, 34, 38], "project": [6, 20, 25, 26, 29, 31], "prop": 13, "propag": [1, 12, 38, 39], "properti": [5, 28, 32, 33, 34, 36], "python": [0, 9, 15, 23, 24, 31], "quick": 8, "quickli": [], "r": 31, "random": [10, 11, 28], "raphson": [33, 36, 37], "rate": [25, 34, 39], "read": [9, 31, 32, 34, 35, 36, 37, 38, 39], "real": [6, 21, 31, 38], "recommend": [31, 32, 39], "record": [], "recurr": [4, 12, 37, 38], "reduc": [0, 32, 38], "reduct": 3, "refer": [25, 26], "referenc": 20, "reformul": 2, "regress": [0, 5, 6, 7, 9, 10, 13, 15, 17, 18, 19, 25, 26, 31, 32, 33, 34, 35, 36, 37], "regular": [1, 39], "relat": [], "relev": [30, 32, 37, 39], "relu": [1, 39], "remark": 3, "remind": [6, 8, 26, 31, 32, 33, 34, 38, 39], "replac": [13, 34], "report": [20, 25, 26], "repositori": [15, 35, 36], "requir": [2, 23], "resampl": [6, 19, 25, 35, 36], "rescal": [6, 32], "residu": [32, 33], "resourc": 2, "result": [32, 33, 38, 39], "revers": 38, "revis": [], "revisit": [13, 33, 34, 36, 37], "rewrit": [31, 32, 35], "rewritten": [36, 37], "ridg": [0, 5, 6, 17, 18, 19, 25, 32, 33, 34], "rm": 13, "rmsprop": 34, "role": [], "root": 39, "rule": [12, 34, 38, 39], "rung": 25, "same": [13, 34, 35, 36], "sampl": 11, "scalabl": 34, "scale": [17, 18, 19, 32, 34], "schedul": [31, 39], "schemat": 9, "scheme": 2, "scienc": 31, "scikit": [0, 1, 11, 31, 32, 33, 34, 35, 36, 37, 39], "second": [13, 18, 34], "select": 36, "semest": 29, "sensit": 33, "septemb": [19, 33, 34, 35, 36, 37], "seriou": 38, "session": [33, 34, 35, 36, 37, 38, 39], "set": [0, 2, 3, 9, 12, 15, 27, 31, 32, 33, 38, 39], "setup": 15, "sgd": [13, 34], "should": [1, 39], "show": [], "sigmoid": 39, "similar": [13, 34], "simpl": [0, 4, 9, 13, 18, 31, 32, 33, 34, 36, 38, 39], "simpler": 38, "simplest": 18, "singl": [10, 37, 38], "singular": [5, 11, 32, 33], "size": [32, 33, 34], "sklearn": 16, "slightli": 34, "smarter": 38, "smoothi": [], "sneak": 34, "soft": 8, "softmax": [1, 39], "softwar": [25, 26, 31], "solv": [2, 33, 36, 37], "solver": 13, "some": [13, 24, 32, 33, 36, 38], "sourc": [], "specifi": 2, "speed": 34, "sphinx": [], "split": [0, 15, 32], "squar": [0, 5, 6, 10, 16, 19, 25, 31, 32, 33, 34], "standard": [13, 32, 35], "start": [20, 37], "state": 0, "statist": [5, 6, 23, 28, 31, 35, 36], "steepest": [10, 13, 33], "step": [34, 35, 36], "stochast": [13, 25, 28, 34], "stop": 34, "strongli": [31, 34], "structur": [], "studi": 37, "suggest": [31, 37], "sum": [35, 36, 38, 39], "summari": [29, 31], "superposit": 3, "supervis": [1, 39], "support": 8, "svd": [5, 32, 33], "synthet": [18, 36, 37], "systemat": 3, "t": 32, "take": 16, "taken": [31, 34], "teach": 29, "teacher": [29, 31], "team": [], "technic": 32, "techniqu": [6, 11, 25], "technologi": 23, "tensorflow": [1, 3, 39], "tent": [29, 31], "term": [35, 38, 39], "test": [0, 1, 15, 17, 26, 32, 39], "texmath": [], "text": 31, "textbook": [30, 31], "than": 33, "thank": [], "theorem": [5, 8, 11, 12, 28, 35, 38], "theoret": 34, "theori": 28, "theta": [18, 35], "thi": [21, 22, 31, 38], "three": [38, 39], "through": 38, "time": 34, "tip": [13, 34], "todo": [], "togeth": [12, 38, 39], "tool": [25, 26, 31], "top": [1, 39], "topic": 31, "toward": 11, "trade": [6, 19, 25], "tradeoff": [6, 35, 36], "train": [0, 1, 4, 15, 21, 22, 31, 32, 38, 39], "transform": 3, "translat": [], "tree": [9, 10], "tuesdai": [33, 37, 38, 39], "tune": [1, 39], "two": [3, 8, 22, 23, 36, 37, 38, 39], "type": [2, 4, 12, 31, 37, 38], "uio": 31, "understand": [22, 35, 36], "univers": [12, 30, 38], "unsupervis": 14, "up": [0, 2, 9, 12, 15, 26, 31, 32, 33, 35, 36, 38, 39], "updat": [25, 34, 38, 39], "us": [0, 1, 2, 3, 7, 13, 16, 18, 19, 22, 23, 25, 26, 31, 32, 33, 34, 36, 37, 38, 39], "usag": [34, 39], "v": [3, 34], "valid": [6, 25, 35, 36], "valu": [5, 11, 19, 28, 32, 33, 35, 36], "vanish": 39, "vari": 34, "variabl": [28, 33], "varianc": [6, 19, 25, 35, 36], "variou": [0, 26, 35, 36], "vector": [8, 12, 16, 24, 31, 32, 37], "versu": 31, "video": [34, 35, 36, 37, 38, 39], "view": [0, 4, 10, 32, 38], "virtual": 15, "visual": [1, 9, 39], "wai": [9, 25, 35, 36, 38], "warm": 26, "wave": 2, "we": [31, 34, 38, 39], "wednesdai": [33, 37, 38, 39], "week": [15, 16, 17, 18, 19, 20, 21, 22, 31, 32, 33, 34, 35, 36, 37, 38, 39], "weekli": [], "weight": 39, "welcom": [], "what": [0, 31, 32, 33, 35, 36], "when": 34, "which": [1, 34, 39], "why": [31, 34, 35, 36, 37, 38], "wisconsin": 7, "word": 38, "workflow": [], "wrap": 35, "write": [4, 11, 20, 22, 25, 26, 33, 39], "x": 32, "xgboost": 10, "xor": [37, 39], "yaml": [], "yet": 33, "your": [0, 10, 16, 18, 25, 26, 32], "z_j": [38, 39]}}) |