Welcome to DeepCTR-Torch’s documentation!

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DeepCTR-Torch is a Easy-to-use , Modular and Extendible package of deep-learning based CTR models along with lots of core components layer which can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict().

Let’s Get Started! (Chinese Introduction)

You can read the latest code at https://github.com/shenweichen/DeepCTR-Torch and DeepCTR for tensorflow version.

News

10/18/2020 : Add DCN-M and DCN-Mix . Add EarlyStopping and ModelCheckpoint callbacks(example). Changelog

10/09/2020 : Improve the reproducibility & fix some bugs. Changelog

03/27/2020 : Add DIN and DIEN . Changelog

Indices and tables