This repository contains Python code for the textbook ‘An Introduction to Statistical Learning’ covering foundational ML techniques including linear regression, classification, regularization (Ridge/Lasso), decision trees, SVMs, and unsupervised methods. Each chapter is implemented as a Jupyter notebook with worked examples and exercises from the book.