Compendium-of-free-ML-reading-resources

Why we included this project

Roughly two hundred free books, lecture notes, and papers on machine learning are gathered here, covering the usual foundations in linear algebra and probability as well as deeper territory like deep learning, NLP, causal inference, and time series. The curation is the real value: every entry links straight to a freely available resource by a recognized author, so you are not wading through paywalled or outdated material. The table of contents is grouped by practical topic rather than by tool, which makes it easy to find a solid reference when you need to brush up on a specific area or hand a reading list to a teammate. Students building foundations and practitioners hunting for a quick, reliable reference on a niche topic will both get something out of it.