Other Resources
Other Important Resources
Machine Learning "Pumpkin Book"
- Core value: Detailed derivations of the formulas in Zhihua Zhou's Machine Learning
- Target audience: Learners who want a deep understanding of the mathematical principles behind algorithms
- Highlights: Thorough mathematical derivations and proofs
Li Hongyi Deep Learning Notes
- GitHub repo: https://github.com/datawhalechina/leedl-tutorial
- Core value: Very low barrier to entry; covers virtually every aspect of deep learning
- Target audience: Can be read directly even without prior machine learning knowledge
- Highlights: Friendly to readers with weaker math backgrounds
The "Bible" of Deep Learning
- Authors: Ian Goodfellow, Yoshua Bengio, Aaron Courville
- Highlights: Solid theoretical foundations, mathematically rigorous
- Coverage: Theoretical foundations and mathematical principles of deep learning
- Suitable for: Researchers and advanced practitioners
MIT Deep Learning Textbook
- Official website: https://www.deeplearningbook.org/
- Highlights: Authoritative theoretical reference, academic standard
- Language: English original, high theoretical depth
PKU CSDIY
- Resource link: https://csdiy.wiki/
- Highlights: Self-study guide for computer science, includes a deep learning path
- Coverage: Course recommendations, learning roadmaps, hands-on projects
Video Courses
Gupao Programmer AI Course
- Course: [AI & Machine Learning] 2023 Comprehensive System Tutorial
- Content: Machine learning algorithms, machine learning in practice
- Link: Bilibili Video
- Highlights: Systematic coverage, practice-oriented
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