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Open Source Machine Learning Degree


A set of free resources for learning machine learning, inspired by similar open source degree resources. Find links to books and book-length lecture notes for study.



By Allen Sarkisyan, DataScience, Inc.

Learn machine learning for free, because free is better than not-free.

This website is inspired by the datasciencemasters/go and open-source-cs-degree Github pages. This one is specifically for machine learning and features textbooks, textbook-length lecture notes, and similar materials found with a simple google search. This repository is meant as a general guide and resource for a free education.

Machine learning wordcloud

Note: Please report any broken links as an issue on the Github page. Thanks!

Mathematics

 
Calculus

  • Calculus by Gilbert Strang pdf

Linear Algebra

  • Linear Algebra by Jim Hefferon pdf

More Linear Algebra

  • Linear Algebra Done Right by Sheldon Axler pdf
  • Advanced Linear Algebra by Steven Roman pdf
  • Advanced Linear Algebra by Bruce E. Shapiro pdf

Even More Damn Linear Algebra

Probability and Statistics

  • Introduction to Probability by Charles M. Grinstead and Laurie Snellpdf
  • All of Statistics by Larry Wasserman pdf

Introductory Machine Learning

  • Introduction to Machine Learning by Alex Smola and S.V.N. Vishwanathan pdf
  • Introduction to Machine Learning - The Wikipedia Guide by Nixonite pdf
  • Introduction to Machine Learning by Ethem Alpaydin pdf

Computer Vision

  • Computer Vision: Algorithms and Applications by Richard Szeliski pdf

Reinforcement Learning

  • Introduction to Reinforcement Learning by Sutton and Barto html

Probabilistic Graphical Models

  • A Brief Introduction to Graphical Models and Bayesian Networks by Kevin Murphy pdf html
  • An Introduction to Graphical Models by Kevin Murphy pdf
  • Probabilistic Graphical Models: Principles and Techniques by Koller, Friedman pdf
  • Bayesian Reasoning and Machine Learning by David Barber pdf

Applied Machine Learning

  • Natural Language Processing with Python by Steven Bird et al. pdf (Python 2) html (Python 3)
  • Machine Learning in Action by Peter Harrington pdf
  • An Introduction to Statistical Learning with Applications in R by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani pdf

Machine Learning - HARD MODE

  • Elements of Statistical Learning by Hastie et al. pdf
  • Pattern Recognition and Machine Learning by Christopher M. Bishop pdf
  • Information Theory, Inference, and Learning Algorithms by David J. C. MacKay pdf

Legal Stuff: If you're the original author of any of these books, and would like me to remove the links to your material, just send me an email at programminglinguist@gmail.com.

Bio: Allen Sarkisyan is a data analyst at Data Science, Inc. He has a degree in math, is currently working on chess data analysis, and has a cat companion who probably knows more linear algebra than he does at this point, given her propensity to sleep on his textbooks and notes. Allen can be contacted at programminglinguist@gmail.com.

Original. Reposted with permission.

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