Virtual bookshelf for math and computer science.
面向数学与计算机科学领域的虚拟书架。
- 统计学 第六版
- SQL 必知必会
- SQL 经典实例
- Exploratory Data Analysis with R
- Excel 圣经
- Data Analysis with Python and PySpark
- Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R
- Streaming Data by Andrew G. Psaltis
- 精通特征工程
- 机器学习 西瓜书
- 手把手带你学懂SVM 张皓著
- Data Mining in Drug Discovery
- 机器学习实战
- Machine Learning Yearning 吴恩达著
- R Packages: Organize, Test, Document, and Share Your Code
- 深度学习 花书
- Deep Learning in Biology and Medicine
- Flink 基础教程
- Efficient Processing of Deep Neural Networks
- 神经网络与深度学习 邱锡鹏著
- Drug Design Using Machine Learning
- TensorFlow in Action by Thushan Ganegedara
- 动手学深度学习
- XGBoost with Python
- 数据科学实战
- Data Science for Economics and Finance
- Visual-Data-Storytelling-with-Tableau
- OpenCV计算机视觉编程攻略
- Computer Vision Projects with PyTorch: Design and Develop Production-Grade Models
- Natural Language Processing with Transformers: Building Language Applications with Hugging Face
- 深度学习进阶：自然语言处理
- Applied Time Series Analysis and Forecasting with Python
- NLTK基础教程：用NLTK和Python库构建机器学习应用
- Personalized Machine Learning by Julian McAuley
- Practical Recommender Systems by Kim Falk
- Python Deep Learning: Exploring Deep Learning Technologies and Neural Network Architectures with PyTorch, Keras, and TensorFlow
- Deep Learning with JavaScript: Neural Networks in tensorflow.js
- Transformers for Machine Learning: A Deep Dive
- AI for Computer Architecture: Principles, Practice, and Prospects
- ZooKeeper: Distributed Process Coordination
- Statistical Reinforcement Learning: Modern Machine Learning Approaches
- Interpretable AI: Building Explainable Machine Learning Systems
- Deep Learning Interviews: Real-World Deep Learning Interview Problems & Solutions
- The-Kaggle-Book: Data Analysis and Machine Learning for Competitive Data Science
- Fluent C: Principles, Practices and Patterns
- Modern C by Jens Gustedt
- C++程序设计简明讲义 潘建瑜著
- 数据结构 C++语言版
- 算法竞赛入门经典 第2版
- 算法竞赛入门经典 训练指南
- API Design for C++
- Git 团队协作
- CUDA C 编程权威指南
- Java Programming
- Microservices Patterns: With examples in Java
- 精通 Rust
- Speed Up Your Python with Rust: Optimize Python performance by creating Python pip modules in Rust with PyO3
- Practical Rust Projects: Building Game, Physical Computing, and Machine Learning Applications
- Linux命令行与Shell脚本编程大全
- Linux/UNIX系统编程手册
- 算法新解 刘新宇著
- Algorithms by Jeff Erickson
- 普林斯顿微积分读本 修订版
- Advanced Algorithms and Data Structures
- 数值分析讲义 潘建瑜著
- Elements of Causal Inference: Foundations and Learning Algorithms
- 面向计算机和机器学习的数学全书
- Scientific Computing
- 计算机代数系统的数学原理
- Matrix Algebra: Theory, Computations and Applications in Statistics
- Algorithm Design Manual
- Matrix Computations
- 最优化：建模、算法与理论
- Discrete Mathematics and Its Applications
- A Textbook of Graph Theory
- Kernel Methods for Machine Learning with Math and Python
- 模式识别与机器学习 马春鹏著
- Handbook of Combinatorial Optimization
- 微分几何 彭家贵
- Probabilistic Numerics
- High-Dimensional Probability: An Introduction with Applications in Data Science
- Inside Deep Learning: Math, Algorithms, Models
- Python语言及其应用
- 流畅的Python
- High Performance Python
- Cython - A guide for Python programmers
- Python Cookbook
- Python网络数据采集
- Python网络爬虫权威指南
- Python网络编程攻略
- Python测试驱动开发
- Python Architecture Patterns
- Python源码剖析：深度探索动态语言核心技术
- Directly find the corresponding
pdffile to download. - Open the file from VSCode (download the
vscode-pdfplugin).