Inspired by research background and iterative project process.
- 普林斯顿数学分析读本 李馨译
- Introduction to Algorithms 4th Edition by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest & Clifford Stein
- Algorithms by Jeff Erickson
- 普林斯顿微积分读本 杨爽等译
- Quantum Chemistry: A concise introduction for students of physics, chemistry, biochemistry and materials science by Ajit J Thakkar
- Advanced Algorithms and Data Structures by Marcello La Rocca
- Physical Chemistry: A Molecular Approach by Donald A. McQuarrie & John D. Simon
- Quantum Chemistry by John P. Lowe & Kirk A. Peterson
- Elements of Causal Inference: Foundations and Learning Algorithms by Jonas Peters, Dominik Janzing & Bernhard Scholkopf
- Scientific Computing by Jeffrey R. Chasnov
- 计算机代数系统的数学原理 李超等著
- Numerical Analysis by Richard L. Burden & J. Douglas Faires
- Molecular Quantum Mechanics by Peter Atkins & Ronald Friedman
- Matrix Algebra: Theory, Computations and Applications in Statistics by James E. Gentle
- Modern Quantum Chemistry: Introduction to Advanced Electronic Structure by Attila Szabo & Neil S. Ostlund
- Algorithm Design Manual by Steven S. Skiena
- Lehninger Principles of Biochemistry by David L. Nelson & Michael M. Cox
- Matrix Computations by Gene H. Golub & Charles F. Van Loan
- Molecular Biology 5th Edition by Robert F. Weaver
- 最优化：建模、算法与理论 文再文等著
- Discrete Mathematics and Its Applications by Kenneth H. Rosen
- A Textbook of Graph Theory by R. Balakrishnan & K. Ranganathan
- 模式识别与机器学习 马春鹏著
- Handbook of Combinatorial Optimization by Panos M. Pardalos, Ding-Zhu Du & Ronald L. Graham
- 普林斯顿概率论读本 李馨译
- Probabilistic Numerics: Computation as Machine Learning by Philipp Hennig, Michael A. Osborne & Hans P. Kersting
- High-Dimensional Probability: An Introduction with Applications in Data Science by Roman Vershynin
- Inside Deep Learning: Math, Algorithms, Models by Edward Raff
- C Primer Plus 6th Edition by Stephen Prata
- Modern C by Jens Gustedt
- C++ Primer Plus 6th Edition by Stephen Prata
- Data Structures and Algorithms in C++ by Michael T. Goodrich, Roberto Tamassia & David M. Mount
- 算法竞赛入门经典 刘汝佳编著
- 算法竞赛入门经典-训练指南 刘汝佳等编著
- 统计学（第六版） 贾俊平等著
- SQL 必知必会 钟鸣等译
- SQL 经典实例 刘春辉译
- Excel Bible by Michael Alexander & Dick Kusleika
- Data Analysis with Python and PySpark by Jonathan Rioux
- Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R by Christian Heumann, Michael Schomaker & Shalabh
- Streaming Data by Andrew G. Psaltis
- 精通特征工程 陈光欣译
- 机器学习实战 李锐等译
- Data Mining in Drug Discovery by Rémy D. Hoffmann, Arnaud Gohier & Pavel Pospisil
- R Packages: Organize, Test, Document, and Share Your Code by Hadley Wickham
- Deep Learning in Biology and Medicine by Davide Bacciu, Paulo J.G. Lisboa & Alfredo Velido
- 深度学习 中文花书
- Flink基础教程 王绍翾译
- Efficient Processing of Deep Neural Networks by Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang & Joel Emer
- Drug Design Using Machine Learning by Inamuddin, Tariq Altalhi, Jorddy N. Cruz & Moamen Salah El-Deen Refat
- 神经网络与深度学习 邱锡鹏著
- Data Science for Economics and Finance by Sergio Consoli, Diego Reforgiato Recupero & Michaela Saisana
- 数据科学实战 冯凌秉等译
- Computer Vision Projects with PyTorch: Design and Develop Production-Grade Models by Akshay Kulkarni, Adarsha Shivananda & Nitin Ranjan Sharma
- Natural Language Processing with Transformers: Building Language Applications with Hugging Face by Lewis Tunstall, Leandro von Werra & Thomas Wolf
- 深度学习进阶：自然语言处理 陆宇杰译
- Applied Time Series Analysis and Forecasting with Python by Changquan Huang & Alla Petukhina
- Practical Recommender Systems by Kim Falk
- Deep Learning with JavaScript: Neural Networks in tensorflow.js by Shanqing Cai, Stanley Bileschi, Eric D. Nielsen & Francois Chollet
- Transformers for Machine Learning: A Deep Dive by Uday Kamath, Kenneth L. Graham & Wael Emara
- AI for Computer Architecture: Principles, Practice, and Prospects by Lizhong Chen, Drew Penney & Daniel Jiménez
- ZooKeeper: Distributed Process Coordination by Flavio Junqueira & Benjamin Reed
- Statistical Reinforcement Learning: Modern Machine Learning Approaches by Ralf Herbrich & Thore Graepel
- Interpretable AI: Building Explainable Machine Learning Systems by Ajay Thampi
- The Kaggle Book: Data Analysis and Machine Learning for Competitive Data Science by Konrad Banachewicz & Luca Massaron
- Python语言及其应用 丁嘉瑞等译
- 流畅的Python 安道等译
- High Performance Python by Micha Gorelick & lan Ozsvald
- Cython - A guide for Python programmers by Kurt W. Smith
- Python网络数据采集 陶俊杰等译
- Python网络爬虫权威指南 神烦小宝译
- Python网络编程攻略 安道译
- Python测试驱动开发 安道译
- Python源码剖析：深度探索动态语言核心技术 陈儒著
- Git团队协作 童仲毅译
- CUDA C编程权威指南 颜成钢等译
- Java Programming by Joyce Farrell
- Algorithms in Java 4th by Robert Sedgewick & Kevin Wayne
- Microservices Patterns: With examples in Java by Chris Richardson
- 精通Rust 邓世超译
- Speed Up Your Python with Rust: Optimize Python performance by creating Python pip modules in Rust with PyO3 by Maxwell Flitton
- Linux命令行与Shell脚本编程大全 门佳等译
- AMAI-GmbH/AI-Expert-Roadmap
- linjing-lab/perming
- vinta/awesome-python
- ml-tooling/best-of-ml-python
- fffaraz/awesome-cpp
- rust-unofficial/awesome-rust
- academic/awesome-datascience
- akullpp/awesome-java
- DovAmir/awesome-design-patterns
- linjing-lab/optimtool
- google/objax
- linjing-lab/sortingx
- cn.julialang.org
- pola-rs/polars-book-cn
- lmmentel/awesome-python-chemistry
- qosf/awesome-quantum-software
- keon/awesome-nlp
- binhnguyennus/awesome-scalabilit