Hi there! This repository contains labs rewritten in Python for the book 'An Introduction to Statistical Learning with Applications in R' by James, Witten, Hastie, Tibshirani (2013).

The book is freely available to download at the above link. There is also an online course based on the book if you are interested.

For the labs, the text in the Jupyter notebooks is taken from the book, adapted to the Python code where necessary. I have mainly used statsmodels, sklearn and scipy packages for the ML models, and matplotlib and seaborn for the plotting.

I have also included some handwritten notes to the chapters (good luck with my handwriting) and solutions to the conceptual exercises, which are at the end of the notes for the respective chapters.

Quick links to the labs:

Lab 3
Lab 4
Lab 5
Lab 6.1
Lab 6.2
Lab 6.3
Lab 7
Lab 8
Lab 9
Lab 10.1
Lab 10.2