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

• Provide tf.keras.Model like interface for quick experiment . example
• Provide tensorflow estimator interface for large scale data and distributed training . example
• It is compatible with both tf 1.x and tf 2.x.

Some related projects:

• DeepMatch: https://github.com/shenweichen/DeepMatch
• DeepCTR-Torch: https://github.com/shenweichen/DeepCTR-Torch

Let's Get Started!(Chinese Introduction) and welcome to join us!

• Weichen Shen. (2017). DeepCTR: Easy-to-use,Modular and Extendible package of deep-learning based CTR models. https://github.com/shenweichen/deepctr.

If you find this code useful in your research, please cite it using the following BibTeX:

@misc{shen2017deepctr,
  author = {Weichen Shen},
  title = {DeepCTR: Easy-to-use,Modular and Extendible package of deep-learning based CTR models},
  year = {2017},
  publisher = {GitHub},
  journal = {GitHub Repository},
  howpublished = {\url{https://github.com/shenweichen/deepctr}},
}

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​ ​ Shen Weichen ​ Alibaba Group ​

Zan Shuxun ​ Alibaba Group ​

​ ​ Harshit Pande Amazon ​

​ ​ Lai Mincai ShanghaiTech University ​

​ ​ Li Zichao Peking University ​

​ Tan Tingyi Chongqing University of Posts and Telecommunications ​