cheungdaven/DeepRec

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1160 stars · 290 forks observed · 2026-08-28

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

DeepRec is an open-source Python/TensorFlow toolkit implementing deep learning based recommendation models for rating prediction, top-N item ranking, and sequential recommendation. It provides modular, extensible implementations of research models like AutoRec, NeuMF, NFM, CML, LRML, and Caser to help researchers reproduce state-of-the-art methods.

Use cases

• reproduce deep learning recommendation models from papers
• build a rating prediction model
• implement top-N item ranking recommendations
• run sequential recommendation experiments
• compare collaborative filtering baselines
• learn how neural recommendation models are implemented in TensorFlow

When to choose

• you need reference implementations of published deep recommendation models
• you are doing academic research on recommender systems
• you want an extensible framework to add new recommendation models
• you work with TensorFlow 1.x and Python 3

When to avoid

• you need production-ready recommendation serving at scale
• you require TensorFlow 2.x support
• you need actively maintained code with frequent updates
• you want a turnkey recommender with minimal coding

Facets

library · maturity maintenance

machine-learning deep-learning machine-learning deep-learning data-science python cross-platform recommender-systems tensorflow collaborative-filtering matrix-factorization factorization-machine rating-prediction top-n-recommendation sequential-recommendation research-toolkit algorithms

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