Artificial Intelligence: A Modern Approach by Stuart Russell, Peter Norvig (2020) [book] — The standard AI textbook. Search, logic, planning, learning, language. (copyrighted)
Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville (2016) [book] — The foundational DL textbook. Theory-heavy, still essential. Online
Dive into Deep Learning by Zhang, Lipton, Li, Smola (2023) [book] — Hands-on deep learning with code and math together. Free and interactive. Online
Pattern Recognition and Machine Learning by Christopher M. Bishop (2006) [book] — Likelihoods, graphical models, and Bayes done properly. (copyrighted)
Reinforcement Learning: An Introduction by Richard Sutton, Andrew Barto (2018) [book] — The RL bible. Bandits to policy gradients to planning. PDF
Machine Learning: A Probabilistic Perspective by Kevin P. Murphy (2012) [book] — Comprehensive ML from a probabilistic viewpoint. The reference encyclopedia. (copyrighted)
Bayesian Reasoning and Machine Learning by David Barber (2012) [book] — Graphical models, inference algorithms, and ML from a Bayesian lens. PDF
The Elements of Statistical Learning by Hastie, Tibshirani, Friedman (2009) [book] — The theory book behind ISLR. Rigorous and comprehensive. Online