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DeepMatch is an open-source deep matching library built for recommendation and advertising systems. It helps developers train models that learn vector representations for users and items. These representations can be exported and used in approximate nearest neighbor search for large-scale retrieval. The library supports familiar Keras workflows through model.fit() and model.predict(). Its model collection includes FM, DSSM, YouTubeDNN, NCF, SDM, MIND, and ComiRec. It is designed to make matching-model experimentation, training, and representation export easier within TensorFlow-based projects.
Features
- User and item representation learning
- Representation vector export for ANN search
- Keras model.fit() and model.predict() workflows
- Multiple deep matching and recommendation models
- TensorFlow-based model development
- Examples and documentation for model training
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Apache License V2.0Follow DeepMatch
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