PaddlePaddle/PaddleRec
A large-scale library of recommendation system algorithms including DeepFM, BERT4Rec, DSSM, and multi-task learning models built with PaddlePaddle.
Not currently ranked — collecting fresh signals.
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PaddleRec provides implementations of classic and state-of-the-art recommendation algorithms for both recall and ranking stages, including Wide&Deep, DeepFM, DIEN, MMoE, and GNN-based models. It includes built-in support for popular recommendation datasets like Criteo and MovieLens, and offers training configurations and model hyperparameter tuning tools for production and research use cases.
Frequently asked
- What is PaddlePaddle/PaddleRec?
- A large-scale library of recommendation system algorithms including DeepFM, BERT4Rec, DSSM, and multi-task learning models built with PaddlePaddle.
- Is PaddleRec open source?
- Yes — PaddlePaddle/PaddleRec is open source, released under the Apache-2.0 license.
- What language is PaddleRec written in?
- PaddlePaddle/PaddleRec is primarily written in Python.
- How popular is PaddleRec?
- PaddlePaddle/PaddleRec has 4.1k stars on GitHub.
- Where can I find PaddleRec?
- PaddlePaddle/PaddleRec is on GitHub at https://github.com/PaddlePaddle/PaddleRec.