Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

Recommendation Algorithm大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM，DSIN，SIGN，IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、ESCMM, MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM，TiSAS，AutoFI…

【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

Tensorflow implementation of DeepFM for CTR prediction.

Recommender Learning with Tensorflow2.x

A framework for large scale recommendation algorithms.

Factorization Machine models in PyTorch

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

TensorFlow Script

DeepTables: Deep-learning Toolkit for Tabular data

原理解析及代码实战，推荐算法也可以很简单 🔥 想要系统的学习推荐算法的小伙伴，欢迎 Star 或者 Fork 到自己仓库进行学习🚀 有任何疑问欢迎提 Issues，也可加文末的联系方式向我询问！

Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)

练习下用pytorch来复现下经典的推荐系统模型, 如MF, FM, DeepConn, MMOE, PLE, DeepFM, NFM, DCN, AFM, AutoInt, ONN, FiBiNET, DCN-v2, AFN, DCAP等

MLGB is a library that includes many models of CTR Prediction & Recommender System by TensorFlow & PyTorch. MLGB是一个包含50+点击率预估和推荐系统深度模型的、通过TensorFlow和PyTorch撰写的库。

A PyTorch implementation of DeepFM for CTR prediction problem.

CTR模型代码和学习笔记总结

4th Place Solution for Mercari Price Suggestion Competition on Kaggle using DeepFM variant.

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Implements of Awesome RecSystem Models with PyTorch/TF2.0

Deep-Learning based CTR models implemented by PyTorch