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'An Introduction to Statistical Learning with Applications in R'http://www-bcf.usc.edu/%7Egareth/ISL/index.html
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Chapter 3 - Linear Regressionhttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%203.ipynb
Chapter 4 - Classificationhttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%204.ipynb
Chapter 5 - Resampling Methodshttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%205.ipynb
Chapter 6 - Linear Model Selection and Regularizationhttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%206.ipynb
Chapter 7 - Moving Beyond Linearityhttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%207.ipynb
Chapter 8 - Tree-Based Methodshttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%208.ipynb
Chapter 9 - Support Vector Machineshttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%209.ipynb
Chapter 10 - Unsupervised Learninghttp://nbviewer.ipython.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Chapter%2010.ipynb
Extra: Misclassification rate simulation - SVM and Logistic Regressionhttp://nbviewer.jupyter.org/github/JWarmenhoven/ISL-python/blob/master/Notebooks/Simulate.expected.misclassification.rate.ipynb
R-package ISLRhttps://cran.r-project.org/web/packages/ISLR/index.html
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http://www-bcf.usc.edu/~gareth/ISL/index.htmlhttp://www-bcf.usc.edu/~gareth/ISL/index.html
http://statweb.stanford.edu/~tibs/ElemStatLearn/http://statweb.stanford.edu/~tibs/ElemStatLearn/
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