计算机网络: 自顶向下方法
James F. Kurose & Keith W. Ross
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches
Stefano V. Albrecht & Filippos Christianos & Lukas Schäfer
The Landscapes of Science and Religion: What Are We Disagreeing ...
Nick Spencer & Hannah Waite
Heard on the Street: Quantitative Questions From Wall Street ...
Timothy Falcon Crack
Bayesian Data Analysis
Andrew Gelman
Statistical Rethinking: A Bayesian Course With Examples in R ...
Richard McElreath
Pen and Paper Exercises in Machine Learning
Michael U. Gutmann
Collection of Problems in Probability Theory
L. D. Meshalkin
Forecasting Economic Time Series
C. W. J. Granger & Paul Newbold & Karl Shell
Information Theory, Inference and Learning Algorithms
David J. C. MacKay
Probabilistic Graphical Models: Principles and Techniques
Daphne Koller & Nir Friedman
Information Geometry and Its Applications
Shun-Ichi Amari
Machine Learning, Second Edition: A Probabilistic Perspective
Kevin P. Murphy