recommender-system
There are 4296 repositories under recommender-system topic.
d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
qdrant/qdrant
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/
weaviate/weaviate
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.
gorse-io/gorse
Gorse open source recommender system engine
hongleizhang/RSPapers
RSTutorials: A Curated List of Must-read Papers on Recommender System.
lancedb/lancedb
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
datawhalechina/fun-rec
推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/
lyst/lightfm
A Python implementation of LightFM, a hybrid recommendation algorithm.
wzhe06/Ad-papers
Papers on Computational Advertising
benfred/implicit
Fast Python Collaborative Filtering for Implicit Feedback Datasets
alibaba/Alink
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
wzhe06/Reco-papers
Classic papers and resources on recommendation
catalyst-team/catalyst
Accelerated deep learning R&D
PaddlePaddle/awesome-DeepLearning
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
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
maciejkula/spotlight
Deep recommender models using PyTorch.
eugeneyan/ml-surveys
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
robi56/Deep-Learning-for-Recommendation-Systems
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
hora-search/hora
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
wzhe06/SparrowRecSys
A Deep Learning Recommender System
unum-cloud/usearch
Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍
pytorch/torchrec
Pytorch domain library for recommendation systems
mJackie/RecSys
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
tensorflow/recommenders
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
ZiyaoGeng/RecLearn
Recommender Learning with Tensorflow2.x
alibaba/EasyRec
A framework for large scale recommendation algorithms.
hexiangnan/neural_collaborative_filtering
Neural Collaborative Filtering
Coder-Yu/QRec
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising
Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.
WLiK/LLM4Rec-Awesome-Papers
A list of awesome papers and resources of recommender system on large language model (LLM).
SeldonIO/seldon-server
Machine Learning Platform and Recommendation Engine built on Kubernetes
jfkirk/tensorrec
A TensorFlow recommendation algorithm and framework in Python.
NVIDIA-Merlin/Transformers4Rec
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
xiangwang1223/knowledge_graph_attention_network
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
ibayer/fastFM
fastFM: A Library for Factorization Machines
NVIDIA-Merlin/NVTabular
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.