Best Practices on Recommendation Systems

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

Officially maintained, supported by PaddlePaddle, including CV, NLP, Speech, Rec, TS, big models and so on.

A Python scikit for building and analyzing recommender systems

Fast Python Collaborative Filtering for Implicit Feedback Datasets

Classic papers and resources on recommendation

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

基于金融-司法领域(兼有闲聊性质)的聊天机器人，其中的主要模块有信息抽取、NLU、NLG、知识图谱等，并且利用Django整合了前端展示,目前已经封装了nlp和kg的restful接口

An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.

推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction

An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)

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

Neural Graph Collaborative Filtering, SIGIR2019

This repository includes some papers that I have read or which I think may be very interesting.

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

“Chorus” of recommendation models: a light and flexible PyTorch framework for Top-K recommendation.

CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).

OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms

Papers about recommendation systems that I am interested in

RecDB is a recommendation engine built entirely inside PostgreSQL