Matrix Calculus (for Machine Learning and Beyond)
Alan Edelman, Steven G. Johnson
Beginning Mathematical Logic: A Study Guide
Peter Smith
Effective C++:改善程序与设计的55个具体做法
Scott Meyers
编译原理
Alfred V. Aho
Pattern Recognition and Machine Learning: Solutions to Exercises ...
Markus Svensén & Christopher M. Bishop
Pattern Recognition and Machine Learning
Christopher M. Bishop
Machine Learning, Second Edition: A Probabilistic Perspective
Kevin P. Murphy
Pen and Paper Exercises in Machine Learning
Michael U. Gutmann
Computer Vision: Models, Learning, and Inference
Simon J. D. Prince
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman
Statistical Rethinking: A Bayesian Course With Examples in R ...
Richard McElreath
Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Physics-based Deep Learning
N. Thuerey, B. Holzschuh, P. Holl, G. Kohl, M. Lino, Q. Liu, ...
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer
Hyperparameter Optimization in Machine Learning
Luca Franceschi