Matrix Calculus (for Machine Learning and Beyond)
Alan Edelman, Steven G. Johnson
Pattern Recognition and Machine Learning
Christopher M. Bishop
Introduction to Algorithms, Third Edition
Thomas H. Cormen & Charles E. Leiserson & Ronald L. Rivest & Clifford Stein
Everything You Always Wanted To Know About Mathematics
Brendan W. Sullivan
Learning Theory From First Principles
Francis Bach
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer
Proof and the Art of Mathematics: Examples and Extensions
Joel David Hamkins
Machine Learning, Second Edition: A Probabilistic Perspective
Kevin P. Murphy
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman