All kinds of tools and books that technical people must read

One, the front end

Must-see tool books:

1. "JavaScript Advanced Programming" ([America] Nicholas)
2. "Illustrated HTTP" ([日] Ueno Nobuyuki)
3. "React Advancement Road" (Xu Chao)
4. "Design Patterns" ([America] Erich Gamma)
5. "The Way to Clean Code" ([America] Robert C. Martin)
6. "CSS World" (Zhang Xinxu)
7. "JavaScript Design Patterns and Development Practice" (Zeng Tan)
8. "JavaScript Functional Programming Guide" ([US] Luis Artesio)
9. "Introduction to Node.js" (Park Ling)
10. "Mastering CSS: Advanced Web Standard Solutions" ([English] Andy Budd)
11. "CSS Authority Guide" ([US] Eric A.Meyer)

Second, the back end

Must-see tool books:

1. "Code for Efficient Java Development Manual" (Yang Guanbao)
2. "In-depth understanding of the Java virtual machine" (Zhou Zhiming)
3. "The Beauty of Mathematics" (Wu Jun)
4. "Top of the Wave" (Wu Jun)
5. "Redis Actual Combat" (translated by Josiah Carlson and Huang Jianhong)
6. "Java Programming Thought" (translated by Bruce Eckel and Chen Haopeng)
7. "Reconstruction" ([America] Martin Fowler)
8. "Scrum and XP in the Smoke" (translated by [Sweden] Kriberg and Li Jian)
9. "Head First Design Pattern" ([US] Freeman)
10. "Effective Java" (translated by Joshua Bloch and Yu Limin)
11. "In-depth understanding of the Java virtual machine" (Zhou Zhiming)

Three, the client

Must-see tool books:

1. "App Architect Practice Guide" (SkySeraph)
2. "Mobile app performance optimization and evaluation" (TMQ special test team)
3. "Mobile App Testing Actual Combat" (Qiu Peng/ Chen Ji/ Pan Xiaoming)
4. "Effective Objective-C 2.0 52 effective ways to write high-quality iOS and OS X code" ([English] Matt Galloway)
5. "In-depth analysis of Mac OS X & iOS operating system" ([US] Levine)
6. "Refactoring: Improving the Design of Existing Code" ([US] Fowler)
7. "Kotlin Core Programming" (Waterdrop Technical Team)
8. "JavaScript Advanced Programming" ([America] Nicholas Zekas)
9. "C++ primer plus" ([America] Stephen Prata)

Fourth, the server

Must-see tool books:

1. "Programmer Practice" ([America] David Thomas)
2. "Domain Driven Design" ([US] Eric Evans)
3. "Microservice Architecture Design" ([US] Chris Richardson)
4. "Kubernetes Authority Guide" (Gong Zheng)
5. "Alibaba Cloud Cloud Native Architecture Practice" (Alibaba Cloud Intelligent Business Group Cloud Native Application Platform of Alibaba Group)
6. "Effective Java Chinese Edition" (Yu Limin)
7. "The Way to Clean Architecture" ([America] Robert C. Martin)
8. "Java Concurrent Programming Actual Combat" ([America] Brian Goetz)
9. "Pyramid Principle: The Logic of Thinking, Expression, and Problem Solving" ([US] Barbara Minto)

Five, test

Must-see tool books:

1. "Best Practices in Automated Testing" ([US] Dorothy Graham / Mark Fewster)
2. "The Way to Clean Code" ([America] Robert C. Martin)
3. "The Way to Clean Architecture" ([America] Robert C. Martin)
4. "Google Software Testing Way" (Huang Li/Li Zhongjie/Xue Ming)
5. "Effective Java Chinese Edition" (Yu Limin)
6. "Google SRE Operation and Maintenance Decryption" ([US] Betsy Beyer)
7. "In-depth understanding of the java virtual machine" (Zhou Zhiming)
8. "Programming Pearls" ([America] Jon Bentley)
9. "Test Engineer Full-stack Technology Advancement and Practice" (Ru Bingsheng)

6. Multimedia technology

Must-see tool books:

1. High Efficiency Video Coding (HEVC) Algorithms and Architectures
2. Audio Signal Processing and Coding, Andreas Spanias
3. Fundamentals of Music Processing, Meinard Müller
4. An Introduction to Audio Content Analysis: Applications in Signal Processing and Music Informatics, Alexander Lerch
5. "Opengl Programming Guide" ([US] Schleier)
6. "Digital Image Processing" ([America] Gonzalez)
7. "Advanced Guide for Audio and Video Development" (Zhan Xiaokai / Wei Xiaohong)
8. "A New Generation of High-Efficiency Video Coding H.265/HEVC: Principles, Standards and Implementation" (Wan Shuai, Yang Fuzheng)
9. "FFmpeg from entry to master" (Liu Qi / Zhao Wenjie)
10. "WebRTC Native Development Actual Combat" (Xu Jianlin)
11. "Digital Audio Principles and Applications Third Edition" (Lu Guanming, Zongfang)
12. "Principles of Digital Video Coding Technology" (Gao Wen)

Seven, computer vision

Must-see tool books:

1. pattern recognition and machine learning , Christopher Bishop
2. Machine Learning: A Probabilistic Perspective ，Murphy
3. Deep Learning， Bengio
4. GANs in Action, Jakub Langr and Vladimir Bok
5. "Digital Image Processing" Third Edition ([US] Gonzalez)
6. "Advanced Programming in the Unix Environment" Third Edition ([US] Stevens)
7. "Computer Vision-Algorithms and Applications" ([US] Szelisk)
8. "Deep Learning Recommendation System" (Wang Zhe)
9. "Machine Learning" (Zhou Zhihua)
10. "Statistical Learning Methods" (Li Hang)
11. "Deep Learning Easy to Learn" (Feng Chao)
12. "Practice Deep Learning" (Li Mu)

8. Data mining and data analysis

Must-see tool books:

1. "Introduction to Data Mining" ([US] Pang-Ning Tan)
2. "Machine Learning" (Zhou Zhihua)
3. "In-depth understanding of data analysis" ([America] Michael Milton)

Nine, recommendation system

Must-see tool books:

1. Deep Learning, Ian Goodfellow
2. "Deep Learning Recommendation System" (Wang Zhe)
3. "Recommended System Practice" (Xiang Liang)
4. "Building an enterprise-level recommendation system from scratch" (Zhang Xiangyu)
5. "Machine Learning" (Zhou Zhihua)

10. 3D&AR

Must-see tool books:

1. "Game Engine Architecture" ([US] Jason Gregory)
2. "More Effective C++" ([US] Scott Meyers)
3. "Computational Geometry: Algorithms and Applications" (Translator: Deng Junhui)
4. Physically Based Rendering: From Theory to Implementation, Matt Pharr, Wenzel Jakob, Greg Humphreys
5. Fundamentals Of Computer Graphics , Peter Shirley
6. Real-Time Rendering, Fourth Edition， Tomas Akenine-Möller, Eric Haines, Naty Hoffman
7. Deep Learning with Python, François Chollet

The content of this information is more than 50 engineers from the Alibaba Tao Department of technology. Through their own learning and growth and technological improvement experience, they share the knowledge books, open courses, open source projects, information forums and other learning resources that they think are most worth learning.

Below we are divided into computer vision, recommendation systems, data mining and data analysis, multimedia-related technologies, testing, front-end, server, client, back-end, and 3D&AR, a total of 10 popular technology fields, I hope to be helpful to you.

Note: The applicable people of this learning resource map are mainly technical groups, which are positioned as the growth direction of beginners to middle and high-end. People with zero basic or non-technical background will have greater difficulty in learning.