An Introduction to Statistical Learning in R.

This book provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist

1. Introduction
2. Statistical Learning
3. Linear Regression
4. Classification
5. Resampling Methods
6. Linear Model Selection and Regularization
7. Moving Beyond Linearity
8. Tree-Based Methods
9. Support Vector Machines
10. Unsupervised Learning

20171205 First review

20180301 Second review

20190105 Third review

20190407 Forth review

20191226 Fifth review