Popular GitHub Repositories for Ctr

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

A unified, comprehensive and efficient recommendation library

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

A framework for large scale recommendation algorithms.

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

Recommender Learning with Tensorflow2.x

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

Factorization Machine models in PyTorch

HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training

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

A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.

Recommender Systems Paperlist that I am interested in

Paper List for Recommend-system PreTrained Models

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM, xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... （pytorch, tf2.0）

Deep-Learning based CTR models implemented by PyTorch

A highly-modularized and recommendation-efficient recommendation library based on PyTorch.

Large batch training of CTR models based on DeepCTR with CowClip.

rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.