Matrix Calculus (for Machine Learning and Beyond)
Alan Edelman, Steven G. Johnson
Hyperparameter Optimization in Machine Learning
Luca Franceschi
Electromagnetic Wave Theory
Jin Au Kong
计算理论导引
Michael Sipser
Entropy and Diversity: The Axiomatic Approach
Tom Leinster
Recommender Systems: The Textbook
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Filtering and System Identification: A Least Squares Approach
Michel Verhaegen & Vincent Verdult
Heard on the Street: Quantitative Questions From Wall Street ...
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Combinatorial Optimization: Theory and Algorithms
Bernhard Korte & Jens Vygen
Algorithms and Combinatorics (1)
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Numerical Optimization
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Springer Series in Operations Research (1)
Algorithms for Convex Optimization
Nisheeth K. Vishnoi
Forecasting Economic Time Series
C. W. J. Granger & Paul Newbold & Karl Shell
矩阵计算
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The Matrix Cookbook
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Introduction to Linear Algebra 5th Edition
Gilbert Strang
Mathematical Thinking: Problem-Solving and Proofs 2nd Edition
John P. D'Angelo & Douglas Brent West
Computers and Intractability: A Guide to the Theory of NP-completeness
Michael R. Garey & David S. Johnson
Python工匠：案例、技巧与工程实践
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多处理器编程的艺术
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流畅的Python
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More Effective C++：35个改善编程与设计的有效方法
Scott Meyers
Effective C++：改善程序与设计的55个具体做法
算法导论
Thomas H. Cormen
算法
Robert Sedgewick & Kevin Wayne
Introduction to Algorithms, Third Edition
Thomas H. Cormen & Charles E. Leiserson & Ronald L. Rivest & Clifford Stein
Introduction to the Theory of Computation (Third Edition): Ji ...
算法设计
Jon Kleinberg
Algorithm Design
Jon Kleinberg & Éva Tardos
深入理解计算机系统
Randal E. Bryant
斯坦福算法博弈论二十讲
Tim Roughgarden
计算机网络: 自顶向下方法
James F. Kurose & Keith W. Ross
零信任网络: 在不可信网络中构建安全系统
Evan Gilman
编程珠玑
Jon Bentley
编译原理
Alfred V. Aho
Computer Systems: A Programmer's Perspective Plus Masteringengineering ...
Randal E. Bryant & David R. O'Hallaron
Matrix Computations
Gene Howard Golub & Charles F. van Loan
C++ Primer Plus
Stephen Prata
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
Proximal Algorithms
Neal Parikh & Stephen P. Boyd & Now Publishers
Information Retrieval: Implementing and Evaluating Search Engines
Stefan Buttcher & Charles L. A. Clarke & Gordon V. Cormack
Non-Convex Optimization for Machine Learning
Prateek Jain & Purushottam Kar
Information Theory, Inference and Learning Algorithms
David J. C. MacKay