A unified, comprehensive and efficient recommendation library

Fast Python Collaborative Filtering for Implicit Feedback Datasets

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.

Neural Collaborative Filtering

Deep learning for recommender systems

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

Factorization Machine models in PyTorch

Next RecSys Library

A Comparative Framework for Multimodal Recommender Systems

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.

Neural Graph Collaborative Filtering, SIGIR2019

Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)

[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"

Versatile End-to-End Recommender System

[WWW'2024] "RLMRec: Representation Learning with Large Language Models for Recommendation"

A developing recommender system in tensorflow2. Algorithm: UserCF, ItemCF, LFM, SLIM, GMF, MLP, NeuMF, FM, DeepFM, MKR, RippleNet, KGCN and so on.

Book recommender system using collaborative filtering based on Spark

BARS: Towards Open Benchmarking for Recommender Systems https://openbenchmark.github.io/BARS

A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models

Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username