Beginning Mathematical Logic: A Study Guide
Peter Smith
Pattern Recognition and Machine Learning
Christopher M. Bishop
Bayesian Data Analysis
Andrew Gelman
Everything You Always Wanted To Know About Mathematics
Brendan W. Sullivan
Matrix Calculus (for Machine Learning and Beyond)
Alan Edelman, Steven G. Johnson
Hyperparameter Optimization in Machine Learning
Luca Franceschi
Physics-based Deep Learning
N. Thuerey, B. Holzschuh, P. Holl, G. Kohl, M. Lino, Q. Liu, ...
Statistical Rethinking: A Bayesian Course With Examples in R ...
Richard McElreath
Pen and Paper Exercises in Machine Learning
Michael U. Gutmann
Pattern Recognition and Machine Learning: Solutions to Exercises ...
Markus Svensén & Christopher M. Bishop
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman
Computer Vision: Models, Learning, and Inference
Simon J. D. Prince
Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Machine Learning, Second Edition: A Probabilistic Perspective
Kevin P. Murphy
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer