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GitHub - shenweichen/DeepCTR-Torch: 【PyTorch】Easy-to-use,Modular and Extendibl...

 4 years ago
source link: https://github.com/shenweichen/DeepCTR-Torch
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README.md

DeepCTR-Torch

Python Versions Downloads PyPI Version GitHub Issues

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PyTorch version of DeepCTR.

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 build your own custom model easily.You can use any complex model with model.fit()and model.predict() .Install through pip install -U deepctr-torch.

Let's Get Started!(Chinese Introduction)

Contributors(welcome to join us!)

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Models List

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 [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 AutoInt [arxiv 2018]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

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