Papers on Computational Advertising
A unified, comprehensive and efficient recommendation library
Tensorflow implementation of DeepFM for CTR prediction.
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
Recommender Learning with Tensorflow2.x
A framework for large scale recommendation algorithms.
Factorization Machine models in PyTorch
A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io
CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)
CTR prediction model based on spark(LR, GBDT, DNN)
TensorFlow Script
DeepTables: Deep-learning Toolkit for Tabular data
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。
Recommender Systems Paperlist that I am interested in
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
A PyTorch implementation of DeepFM for CTR prediction problem.
CTR模型代码和学习笔记总结
Tensorflow implementation of Product-based Neural Networks. An extended version is at https://github.com/Atomu2014/product-nets-distributed.
BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS
Paper List for Recommend-system PreTrained Models
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