https://github.com/millionintegrals/esl

Algorithms from the book "Elements of Statistical Learning", implemented in Python
https://github.com/millionintegrals/esl

Last synced: 12 months ago
JSON representation

Algorithms from the book "Elements of Statistical Learning", implemented in Python

• Host: GitHub
• URL: https://github.com/millionintegrals/esl
• Owner: MillionIntegrals
• License: mit
• Created: 2014-05-10T20:12:29.000Z (about 12 years ago)
• Default Branch: master
• Last Pushed: 2015-03-29T17:19:01.000Z (about 11 years ago)
• Last Synced: 2025-03-17T04:36:00.401Z (over 1 year ago)
• Language: Python
• Homepage: millionintegrals.com
• Size: 242 KB
• Stars: 10
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
ESL

===

Algorithms from the book "Elements of Statistical Learning", implemented in Python.

Most algorithms are implemented in a very inefficient manner as the goal is to aim for maximum readability.

I've tried to make the code be easy to follow and figure out what it is doing. I hope you like it.

- Book website: http://statweb.stanford.edu/~tibs/ElemStatLearn/

- Repository link: https://github.com/MillionIntegrals/ESL

## Required packages

You need to have following packages installed on your system to run these examples:

- numpy

- pandas