ML Resources

Here are some semi-organized ML and ML-elated resources.

ML Books

• Machine Learning – A First Course for Engineers and Scientists

Datasets

• Open ML

Posts and Tutorials

• Bayes’ Theorem with Legos
• Lecture Notes from Stanford ML course by Andrew Ng
  • Supervised Learning
• Linear Algebra Review and Reference

Python

• Dr Andrew Harrington – Hands-On Python Tutorial Release 2.0
• Jake VanderPlas – A Whirl-wind Tour of Python (from around 2016)
  • also available as a set of Jupyter Notebooks.
  • Jake is also the author of Python Data Science Handbook from O’Reilly Press

Collections of Resources by Others

• Data Labs at Tufts