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

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

Recommender Learning with Tensorflow2.x

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)

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。

CTR模型代码和学习笔记总结

Implements of Awesome RecSystem Models with PyTorch/TF2.0

主流推荐系统Rank算法的实现

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

some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network

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

rater, recommender systems. 推荐模型，包括：DeepFM，Wide&Deep，DIN，DeepWalk，Node2Vec等模型实现，开箱即用。

一些CTR模型和常见特征工程的方法

A easy library for recommendation system or computational advertising

2018腾讯社交广告33名；

AlitaNet: A click through rate (ctr) prediction deep learning Network implementation with TensorFlow, including LR, FM, AFM, Wide&Deep, DeepFM, xDeepFM, AutoInt, FiBiNet, LS-PLM, DCN, etc.

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

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