Free Textbook: Introduction to Machine Learning Covers the Math from Optimization to Generative Models
TheTuringPost · x · 2026-10-16
Turing Post recommends Introduction to Machine Learning by Laurent Younes (arXiv:2409.02668, v2 updated May 2025). The free textbook builds the mathematical foundations of ML, covering matrix analysis, optimization (SGD, proximal methods), Adam, bias–variance, regression and kernels, SVMs, decision trees, boosting, and neural networks, plus Markov-chain sampling, graphical models, variational methods, deep generative models, and unsupervised methods like clustering and manifold learning. A solid next step if you already know core ML concepts.
Related event: JHU's Laurent Younes Releases Free Machine Learning Textbook(2 posts)→
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