ISLR

My Python coding for labs and applied exercises in the book An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie, Tibshirani.

Development environment:

Python libraries used:

Reference: Elements of Statistical Learning by Hastie, T., Tibshirani, R., Friedman, J.

Name		Name	Last commit message	Last commit date
Latest commit History 28 Commits
.gitignore		.gitignore
Chapter 10 Unsupervised Learning.ipynb		Chapter 10 Unsupervised Learning.ipynb
Chapter 3 Linear Regression.ipynb		Chapter 3 Linear Regression.ipynb
Chapter 4 Classification.ipynb		Chapter 4 Classification.ipynb
Chapter 5 Resampling Methods.ipynb		Chapter 5 Resampling Methods.ipynb
Chapter 6 Linear Model Selection and Regularization.ipynb		Chapter 6 Linear Model Selection and Regularization.ipynb
Chapter 7 Moving Beyond Linearity.ipynb		Chapter 7 Moving Beyond Linearity.ipynb
Chapter 8 Tree-Based Methods.ipynb		Chapter 8 Tree-Based Methods.ipynb
Chapter 9 Support Vector Machines.ipynb		Chapter 9 Support Vector Machines.ipynb
README.md		README.md

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