基于PyTorch的基于深度学习的CTR(Click-Through Rate)预测模型的易用、模块化和可扩展包

deepctr-torch的Python项目详细描述


DeepCTR火炬

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DeepCTR的Pythorch版本。在

DeepCTR是一个易于使用的模块化可扩展的软件包,包括基于深度学习的CTR模型以及许多可用于构建自己定制模型的核心组件层很容易。你可以使用带有model.fit()model.predict()的任何复杂模型。通过pip install -U deepctr-torch安装。在

让我们Get Started!Chinese Introduction

型号列表

ModelPaper
Convolutional Click Prediction Model[CIKM 2015]A Convolutional Click Prediction Model
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[DLRS 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
xDeepFM[KDD 2018]xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems
Deep Interest Network[KDD 2018]Deep Interest Network for Click-Through Rate Prediction
Deep Interest Evolution Network[AAAI 2019]Deep Interest Evolution Network for Click-Through Rate Prediction
AutoInt[CIKM 2019]AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
ONN[arxiv 2019]Operation-aware Neural Networks for User Response Prediction
FiBiNET[RecSys 2019]FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction
DCN-M[arxiv 2020]DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems

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