A easy library for recommendation system or computational advertising

Easy-to-use pytorch-based framework for RecSys models

Deep-learning based CTR models implemented with tensorflow2.0. / 使用tensorflow2.0实现的一些基于深度学习的CTR模型

一些CTR模型和常见特征工程的方法

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！

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

Explicit high order interaction models implemented in Keras, including: DCN, xDeepFM, AutoInt etc.

LightCTR is a tensorflow 2.0 based, extensible toolbox for building CTR/CVR predicting models.

Factorization Machine models in PyTorch

Here are the models listed in CTR. Example: FM、DeepFM、xDeepFM etc.

DeepTables: Deep-learning Toolkit for Tabular data

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

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 framework for large scale recommendation algorithms.