There are 117 repositories under recommender-system topic.
An open source recommender system service written in Go
A Curated List of Must-read Papers on Recommender System.
A Python implementation of LightFM, a hybrid recommendation algorithm.
Papers on Computational Advertising
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
Classic papers and resources on recommendation
Accelerated deep learning R&D
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Deep recommender models using PyTorch.
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
An index of algorithms for learning causality with data
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
A Deep Learning Recommender System
Qdrant - vector similarity search engine with extended filtering support
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
Neural Collaborative Filtering
Machine Learning Platform and Recommendation Engine built on Kubernetes
Recommender Learning with Tensorflow2.x
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
A TensorFlow recommendation algorithm and framework in Python.
Pytorch domain library for recommendation systems
fastFM: A Library for Factorization Machines
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.
YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.
The awesome and classic papers in recommendation system!!! Good luck to every RecSys-learner!
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
Neural Graph Collaborative Filtering, SIGIR2019
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
个性化新闻推荐系统，A news recommendation system involving collaborative filtering,content-based recommendation and hot news recommendation, can be adapted easily to be put into use in other circumstances.