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FYS-STK4155/doc/web/tmp_mako__course.do.txt
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mhjensen 9bd71f8050 adding ipynb to projects
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TITLE: Overview of course material: Data Analysis and Machine Learning
AUTHOR: "Morten Hjorth-Jensen":"http://mhjgit.github.io/info/doc/web/" at Department of Physics and Astronomy and Facility for Rare ion Beams and National Superconducting Cyclotron Laboratory, Michigan State University, USA & Department of Physics (office FV308), University of Oslo, Norway
The teaching material is produced in various formats for printing and on-screen reading.
!split
!bwarning
The PDF files are based on LaTeX and have seldom technical
failures that cannot be easily corrected.
The HTML-based files, called ``HTML'' and ``ipynb'' below, apply MathJax
for rendering LaTeX formulas and sometimes this technology gives rise
to unexpected failures (e.g.,
incorrect rendering in a web page despite correct LaTeX syntax in the
formula). Consult the corresponding PDF
files if you find missing or incorrectly rendered
formulas in HTML or ipython notebook files.
!ewarning
===== Basic introduction to the course with schedule etc =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Intro2Course/pdf/Intro2Course-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Intro2Course/html/Intro2Course.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Intro2Course/html/Intro2Course-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Intro2Course/html/Intro2Course-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Intro2Course/ipynb/Intro2Course.ipynb"
===== Introduction to Data Analysis and Machine Learning =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Introduction/pdf/Introduction-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Introduction/html/Introduction.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Introduction/html/Introduction-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Introduction/html/Introduction-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Introduction/ipynb/Introduction.ipynb"
===== Getting started with Machine Learning with simple Examples =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/How2ReadData/pdf/How2ReadData-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/How2ReadData/html/How2ReadData.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/How2ReadData/html/How2ReadData-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/How2ReadData/html/How2ReadData-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/How2ReadData/ipynb/How2ReadData.ipynb"
===== Review of central linear algebra elements =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Linalg/pdf/Linalg-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Linalg/html/Linalg.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Linalg/html/Linalg-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Linalg/html/Linalg-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Linalg/ipynb/Linalg.ipynb"
===== Monte Carlo methods and elements of probability theory =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Statistics/pdf/Statistics-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Statistics/html/Statistics-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Statistics/ipynb/Statistics.ipynb"
===== Regression Methods =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Regression/pdf/Regression-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Regression/html/Regression-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Regression/ipynb/Regression.ipynb"
===== Gradient methods and Minimization Algorithms =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Splines/pdf/Splines-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Splines/html/Splines-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Splines/ipynb/Splines.ipynb"
===== Logistic Regression =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/LogReg/pdf/LogReg-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/LogReg/html/LogReg.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/LogReg/html/LogReg-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/LogReg/html/LogReg-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/LogReg/ipynb/LogReg.ipynb"
===== Neural Networks =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/pdf/NeuralNet-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/html/NeuralNet-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/NeuralNet/ipynb/NeuralNet.ipynb"
===== Convolutional Neural Networks =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/cnn/pdf/cnn-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/cnn/html/cnn.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/cnn/html/cnn-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/cnn/html/cnn-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/cnn/ipynb/cnn.ipynb"
===== Reduction of dimensionality =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/DimRed/pdf/DimRed-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/DimRed/html/DimRed.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/DimRed/html/DimRed-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/DimRed/html/DimRed-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/DimRed/ipynb/DimRed.ipynb"
===== Decision Trees and Random Forests =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/pdf/DecisionTrees-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/html/DecisionTrees-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/DecisionTrees/ipynb/DecisionTrees.ipynb"
===== Support Vector Machines =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/svm/pdf/svm-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/svm/html/svm-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/svm/ipynb/svm.ipynb"
===== Unsupervised Learning, Boltzmann Machines =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/BM/pdf/BM-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/BM/html/BM-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/BM/ipynb/BM.ipynb"
===== Recurrent Neural Networks =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Recurrent/pdf/Recurrent-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Recurrent/html/Recurrent.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Recurrent/html/Recurrent-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Recurrent/html/Recurrent-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Recurrent/ipynb/Recurrent.ipynb"
===== Autoencoders =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Autoencoders/pdf/Autoencoders-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Autoencoders/html/Autoencoders.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Autoencoders/html/Autoencoders-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Autoencoders/html/Autoencoders-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Autoencoders/ipynb/Autoencoders.ipynb"
===== Reinforcement Learning =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Reinforce/pdf/Reinforce-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Reinforce/html/Reinforce.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Reinforce/html/Reinforce-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Reinforce/html/Reinforce-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Reinforce/ipynb/Reinforce.ipynb"
===== Solving ordinary and Partial Differential Equations and Eigenvalue Problems with Neural Networks =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/odenn/pdf/odenn-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/odenn/html/odenn.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/odenn/html/odenn-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/odenn/html/odenn-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/odenn/ipynb/odenn.ipynb"
===== Elements of Bayesian theory and Bayesian Neural Networks =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/pdf/Bayesian-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/html/Bayesian-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/Bayesian/ipynb/Bayesian.ipynb"
===== Summary =====
* LaTeX PDF:
* For printing:
* "Standard one-page format": "https://compphysics.github.io/MachineLearning/doc/pub/summary/pdf/summary-minted.pdf"
* HTML:
* "Plain html": "https://compphysics.github.io/MachineLearning/doc/pub/summary/html/summary.html"
* "reveal.js beige slide style": "https://compphysics.github.io/MachineLearning/doc/pub/summary/html/summary-reveal.html"
* "Bootstrap slide style, easy for reading on mobile devices": "https://compphysics.github.io/MachineLearning/doc/pub/summary/html/summary-bs.html"
* Jupyter notebook:
* "ipynb file": "https://compphysics.github.io/MachineLearning/doc/pub/summary/ipynb/summary.ipynb"
!split
===== Projects and Exercises Fall 2020 =====
=== First homework set, week 35 ===
* LaTeX and PDF:
* "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw1/pdf/hw1.tex"
* "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw1/pdf/hw1.pdf"
* HTML:
* "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw1/html/hw1.html"
* "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw1/html/hw1-bs.html"
=== Second homework set, week 36 ===
* LaTeX and PDF:
* "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw2/pdf/hw2.tex"
* "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw2/pdf/hw2.pdf"
* HTML:
* "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw2/html/hw2.html"
* "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/hw2/html/hw2-bs.html"
=== Project 1, Deadline October 5 (available September 1) ===
* LaTeX and PDF:
* "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project1/pdf/Project1.tex"
* "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project1/pdf/Project1.pdf"
* HTML:
* "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project1/html/Project1.html"
* "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project1/html/Project1-bs.html"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project1/ipynb/Project1.ipynb"
=== Project 2, Deadline November 2 (available September 28) ===
* LaTeX and PDF:
* "Latex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project2/pdf/Project2.tex"
* "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project2/pdf/Project2.pdf"
* HTML:
* "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project2/html/Project2.html"
* "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project2/html/Project2-bs.html"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project2/ipynb/Project2.ipynb"
=== Project 3, Deadline December 7 (available November 2) ===
* LaTeX and PDF:
* "LaTex file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project3/pdf/Project3.tex"
* "PDF file":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project3/pdf/Project3.pdf"
* HTML:
* "Plain html":"http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project3/html/Project3.html"
* "Bootstrap slide style, easy for reading on mobile devices": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project3/html/Project3-bs.html"
* Jupyter notebook:
* "ipynb file": "http://compphysics.github.io/MachineLearning/doc/Projects/2020/Project3/ipynb/Project3.ipynb"
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