imsheridan/DeepRec resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1016 stars · 216 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated collection of must-read papers and industry presentations on deep recommendation systems and CTR prediction, organized by topic with a paper structure map. It aggregates classic and cutting-edge research from industry labs like Alibaba, Google, Microsoft, and Huawei.

Use cases

• find must-read papers on recommendation systems
• learn CTR prediction models like DIN and DCN
• study deep learning approaches to computational advertising
• get an overview of recommender system research landscape
• find industry papers on feature interaction and user interest modeling
• explore reinforcement learning in recommendation

When to choose

• you want a curated, organized reading list for recommender systems and CTR prediction
• you need links to original industry papers from top conferences like KDD, WWW, and AAAI
• you are preparing for research or interviews in recommendation/advertising

When to avoid

• you need runnable code or implementations rather than papers
• you want a maintained software library or tool
• you need beginner tutorials rather than research papers

Facets

learning-resource · maturity maintenance

machine-learning deep-learning data-science machine-learning deep-learning tutorials awesome-lists cross-platform recommendation-systems ctr-prediction papers computational-advertising curated-list

Member repositories

For agents

markdown · JSON · MCP: product_card(name="imsheridan/DeepRec")