Popular GitHub Repositories for Recommendations

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

A unified, comprehensive and efficient recommendation library

? Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

All-in-one infrastructure for search, recommendations, RAG, and analytics offered via API

A low code Machine Learning personalized ranking service for articles, listings, search results, recommendations that boosts user engagement. A friendly Learn-to-Rank engine

收集 CVPR 最新的成果，包括论文、代码和demo视频等，欢迎大家推荐！Collect the latest CVPR (Conference on Computer Vision and Pattern Recognition) results, including papers, code, and demo videos, etc., and welcome recommendations from everyone!

A self-hosted stack for media management and streaming, with AI-powered movie and show recommendations. Includes Sonarr, Radarr, qBitTorrent, Prowlarr, Jellyfin, Jellyseerr, Recommendarr, and VPN support.

Modular e-commerce backend with a GraphQL gateway and gRPC microservices for accounts, products, orders, and recommendations.

Recommender Systems Paperlist that I am interested in

HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling

ArXiv Digest and Personalized Recommendations using Large Language Models

Resume-AI: Supercharge your job search! This tool analyzes your resume against job descriptions using Google's Gemini AI to boost your ATS score. Get detailed feedback on missing skills, a professional summary, and actionable recommendations to tailor your resume and land that interview.

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined

Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow

A curated list of resources on cold-start recommendations.

rectorch is a pytorch-based framework for state-of-the-art top-N recommendation

rec_pangu is a flexible open-source project for recommendation systems. It incorporates diverse AI models like ranking algorithms, sequence recall, multi-interest models, and graph-based techniques. Designed for both beginners and advanced users, it enables rapid construction of efficient, custom recommendation engines.

This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to topic where they are consumed by a spark streaming job running on IBM BigInsights (hadoop).