recommender-system

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a cloud-native database​.

Developer-friendly OSS embedded retrieval library for multimodal AI. Search More; Manage Less.

AI powered open source recommender system engine supports classical/LLM rankers and multimodal content via embedding

推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/

RSTutorials: A Curated List of Must-read Papers on Recommender System.

A Python implementation of LightFM, a hybrid recommendation algorithm.

Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

Fast Python Collaborative Filtering for Implicit Feedback Datasets

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

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

An index of algorithms for learning causality with data

A Deep Learning Recommender System

🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .

Pytorch domain library for recommendation systems

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking, Post Ranking, Relevance, LLM and RL. Please cite our paper "Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives" (TOIS 2026).

A framework for large scale recommendation algorithms.

A list of awesome papers and resources of recommender system on large language model (LLM).

TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

Minimal reproduction of OneRec

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.

This is a repository of public data sources for Recommender Systems (RS).

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

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.

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

A Comparative Framework for Multimodal Recommender Systems

A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.