There are 148 repositories under recommender-system topic.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.
Qdrant - Vector Database for the next generation of AI applications. Also available in the cloud https://cloud.qdrant.io/
Gorse open source recommender system engine
Weaviate is an open source vector database that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients.
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.
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Accelerated deep learning R&D
Classic papers and resources on recommendation
Deep recommender models using PyTorch.
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
An index of algorithms for learning causality with data
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
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
A Deep Learning Recommender System
Recommender Learning with Tensorflow2.x
Neural Collaborative Filtering
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Machine Learning Platform and Recommendation Engine built on Kubernetes
Pytorch domain library for recommendation systems
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
A TensorFlow recommendation algorithm and framework in Python.
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.
fastFM: A Library for Factorization Machines
A framework for large scale recommendation algorithms.
YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
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.
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.
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.