/ISLR-python

Python code for Introduction to Statistical Learning

Primary LanguageJupyter Notebook

Introduction to Statistical Learning with Python Code

Introduction

This repository provides Python code for the LABs in the book "Introduction to Statistical Learning" by James, Witten, Hastie, Tibshirani (2013).

Content

The code is presented in Jupyter Notebook and the data is stored in data folder. The content includes:

  1. Chapter 03: Linear Regression
  2. Chapter 04: Classification
  3. Chapter 05: Resampling Methods
  4. Chapter 06: Linear Model Selection and Regularization
  5. Chapter 07: Moving Beyond Linearity
  6. Chapter 08: Tree-Based Methods
  7. Chapter 09: Support Vector Machines
  8. Chapter 10: Unsupervised Learning

Reference

[1] Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani, "An Introduction to Statistical Learning with Applications in R".
[2] Github code: https://github.com/JWarmenhoven/ISLR-python