shenweichen/DeepMatch
A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search. observed · 2026-08-28
Health v2 · maintenance only
72/100
- Activity 78
- Release rhythm 48
- Longevity 100
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: 2340
- days_rel: 137
- days_push: 137
- n_releases_24m: 1
Adoption not part of the score
2433 stars · 541 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
DeepMatch is a Python library of deep matching models for recommendations and advertising, built on TensorFlow/Keras. It lets users train models with fit/predict and export user and item representation vectors for approximate nearest neighbor search.
Use cases
- train a DSSM two-tower matching model for recommendations
- export user and item embedding vectors for ANN retrieval
- implement YouTubeDNN candidate generation for a recommender
- build deep matching models for online advertising
- experiment with MIND and ComiRec multi-interest models
- train factorization-machine style matching models in Python
When to choose
- you need ready implementations of deep matching models like DSSM, YouTubeDNN, or MIND
- you want to export embeddings for vector/ANN search in a recommendation pipeline
- you prefer a Keras-style fit/predict workflow on TensorFlow
When to avoid
- you need a full end-to-end recommender system with serving and ranking, not just matching models
- your stack is PyTorch-based rather than TensorFlow
- you need non-neural or lightweight collaborative filtering only
Facets
library · maturity active
machine-learning deep-learning search-engine machine-learning deep-learning python recommendation-systems matching-models dssm youtubednn ann-search tensorflow advertising collaborative-filtering recommendation
2 sources
- readme: https://github.com/shenweichen/DeepMatch · fetched 2026-08-28 · ab25fc3a2e1e
- registry_pypi: https://pypi.org/pypi/deepmatch/json · fetched 2026-08-29 · 807120747c3d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| shenweichen/DeepMatch | main | 72 |
For agents
markdown · JSON · MCP: product_card(name="shenweichen/DeepMatch")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem