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bookshelf📦

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/C++

  • 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

  • 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

    • Extra

  • 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

    • reference

  • AMAI-GmbH/AI-Expert-Roadmap
  • 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

    • LICENSE

    MIT LICENSE

     
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