#5151st of 55 in Learning and cookbooks
fun-rec
Chinese-language textbook on recommender systems, from cascades to generative models
- Stars
- 7.4k
- License
- no license
- Last commit
- Jun 2026
- Language
- Python
6,846 on 1 Apr 20267,434 on 21 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
An online book (小麦书) on recommender algorithms in two parts. The first covers the cascade pipeline: collaborative filtering, vector and sequence recall, feature crossing, multi-task and multi-scenario ranking, and re-ranking. The second covers generative recommendation (HSTU, OneRec, reasoning and diffusion models) and ends with a production system project. The README gives no setup or run instructions.
Who it is for: Engineers with ML basics learning recommender algorithms, Chinese readers
Strengths
- Covers the path from collaborative filtering to generative recommenders such as HSTU and OneRec
- Final chapter walks through building a production recommender system
- Re-ranking, multi-objective and multi-scenario ranking are covered alongside recall
Weaknesses
- Main README is in Chinese; English version is a separate file
- Under active development, and Pull Requests are not accepted
- CC BY-NC-SA 4.0 license bars commercial use
- README does not list code requirements, datasets or how to run examples
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