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Description: Exercises from 'Introduction to Statistical Learning with Applications in R' written in Python. - ertugguney/IntroStatLearn

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'Introduction to Statistical Learning with Applications in R'http://www-bcf.usc.edu/~gareth/ISL/
Numpyhttp://www.numpy.org/
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https://github.com/ertugguney/IntroStatLearn#chapters
Chapter 2: Statistical Learninghttps://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch2_Statistical_Learning
Chapter 3: Linear Regressionhttps://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch3_Linear_Regression
Chapter 4: Classificationhttps://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch4_Classification
Chapter 5: Resampling Methodshttps://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch5_Resampling_Methods
Chapter 6: Linear Model Selection & Regularizationhttps://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch6_Linear_Model_Selection_Regularization
Chapter 7: Moving Beyond Linearity https://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch7_Moving_Beyond_Linearity
Chapter 8: Tree-Based Methodshttps://github.com/ertugguney/IntroStatLearn/blob/master/notebooks/Ch8_Tree_Methods
Chapter 9: https://github.com/ertugguney/IntroStatLearn/blob/master
Chapter 10:https://github.com/ertugguney/IntroStatLearn/blob/master
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