Mathematics-for-ML

Why we included this project

Developers and data scientists who keep stalling on the math behind their models will find this collection genuinely useful. It pulls together free books, papers, video lectures, and courses that cover the linear algebra, calculus, probability, and optimization used in machine learning. The real value is the editorial judgment: each entry is annotated with hints about where to start, how to get comfortable with notation, or which lectures line up with a specific topic like backpropagation. Since every resource is openly available, from the MML book and Deep Learning textbook to Khan Academy, you can build a solid foundation without paying for a course. Treat it as a study guide, not a piece of software to run.