wangshusen/RecommenderSystem resource
None observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1603
- days_rel: n/a
- days_push: 938
- n_releases_24m: 0
Adoption not part of the score
4174 stars · 537 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A collection of lecture slides, notes, and videos teaching industrial recommender systems, covering retrieval (ItemCF, UserCF, Swing, two-tower models), ranking, and A/B testing. It is an educational resource rather than runnable software.
Use cases
- learn how industrial recommender systems work
- understand collaborative filtering algorithms like ItemCF and UserCF
- study two-tower retrieval models and their training
- learn about A/B testing for recommendation systems
- prepare for machine learning engineer interviews in recommendation
- find course slides and videos on deep retrieval
When to choose
- you want structured course material on recommender system pipelines
- you prefer video lectures with accompanying slides
- you want industry-oriented explanations rather than academic papers
When to avoid
- you need runnable recommender system code or a library
- you need an up-to-date maintained project with a license
- you need content in English
Facets
learning-resource · maturity stable
machine-learning search-engine data-science machine-learning tutorials education big-data cross-platform recommender-systems collaborative-filtering two-tower-model course-materials chinese-language
1 source
- readme: https://github.com/wangshusen/RecommenderSystem · fetched 2026-08-28 · 8aefa1152a74
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| wangshusen/RecommenderSystem | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="wangshusen/RecommenderSystem")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem