Measurement
Paul Lockhart
Introduction to Algorithms, Third Edition
Thomas H. Cormen & Charles E. Leiserson & Ronald L. Rivest & Clifford Stein
Combinatorial Optimization: Theory and Algorithms
Bernhard Korte & Jens Vygen
Algorithms and Combinatorics (1)
Filtering and System Identification: A Least Squares Approach
Michel Verhaegen & Vincent Verdult
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer
Machine Learning, Second Edition: A Probabilistic Perspective
Kevin P. Murphy
Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Pattern Recognition and Machine Learning
Christopher M. Bishop
Computer Vision: Models, Learning, and Inference
Simon J. D. Prince
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman
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