All repos
Jupyter Notebook MIT 19000 3400

dair-ai/Mathematics for Machine Learning

Mathematics for Machine Learning is a curated learning repository that connects the core mathematics behind modern machine learning: linear algebra, calculus, probability, statistics and optimisation. It is a useful roadmap for learners who want concepts, references and practical study order rather than isolated formulas.

Overview

Mathematics for Machine Learning is a curated learning repository that connects the core mathematics behind modern machine learning: linear algebra, calculus, probability, statistics and optimisation. It is a useful roadmap for learners who want concepts, references and practical study order rather than isolated formulas.

What you can do

  • Organise a learning path across the mathematical foundations of ML.
  • Find books, courses, notes and exercises for each subject.
  • Use it to identify gaps before moving to deep learning or research papers.

How to use this repository

  1. Start with the official guide and a small example.
  2. Adapt one example to a real mathematical problem or teaching activity.
  3. Use the GitHub issues and releases to keep up with the project.

Screenshot

Mathematics for Machine Learning GitHub preview

Learning resources