Welcome to DeepMatch’s documentation!

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DeepMatch is a deep matching model library for recommendations, advertising, and search. It’s easy to train models and to export representation vectors for user and item which can be used for ANN search.You can use any complex model with model.fit() and model.predict() .

Let’s Get Started! or Run examples!

You can read the latest code at https://github.com/shenweichen/DeepMatch

News

07/04/2022 : Support different negative sampling strategies, including inbatch , uniform , frequency , adaptive . Changelog

06/17/2022 : Fix some bugs. Changelog

10/12/2020 : Support different initializers for different embedding weights and loading pretrained embeddings. Changelog

Indices and tables