Welcome to DeepMatch’s documentation!

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

05/17/2020 : Add SDM model. Changelog

04/10/2020 : Support saving and loading model . Changelog

04/06/2020 : DeepMatch first version .

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Home:

• Quick-Start
  • Installation Guide
  • Run examples !!
• Features
  • Feature Columns
  • Models
• Examples
  • Run YoutubeDNN on MovieLen1M on Google colab
  • YoutubeDNN/MIND with sampled softmax
  • SDM with sampled softmax
  • DSSM with negative sampling
• FAQ
  • 1. Save or load weights/models
  • 2. Set learning rate and use earlystopping
• History

API:

• Models
  • Model Methods
    • compile
    • fit
    • evaluate
    • predict
    • train_on_batch
    • test_on_batch
    • predict_on_batch
    • fit_generator
    • evaluate_generator
    • predict_generator
    • get_layer
  • FM
  • DSSM
  • YoutubeDNN
  • NCF
  • SDM
  • MIND

Indices and tables

• Index
• Module Index
• Search Page