DeepCTR 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.You can use any complex model with model.fit()andmodel.predict() just like any other keras model.And the layers are compatible with tensorflow.Through pip install deepctr get the package and Get Started!
| Model | Paper |
|---|---|
| Factorization-supported Neural Network | [ECIR 2016]Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction |
| Product-based Neural Network | [ICDM 2016]Product-based neural networks for user response prediction |
| Wide & Deep | [arxiv 2016]Wide & Deep Learning for Recommender Systems |
| DeepFM | [IJCAI 2017]DeepFM: A Factorization-Machine based Neural Network for CTR Prediction |
| Piece-wise Linear Model | [arxiv 2017]Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction |
| Deep & Cross Network | [ADKDD 2017]Deep & Cross Network for Ad Click Predictions |
| Attentional Factorization Machine | [IJCAI 2017]Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks |
| Neural Factorization Machine | [SIGIR 2017]Neural Factorization Machines for Sparse Predictive Analytics |
| Deep Interest Network | [KDD 2018]Deep Interest Network for Click-Through Rate Prediction |