R
recommenders
recommenders-team/recommenders
Best Practices on Recommendation Systems
★21.9kstars
Python
MIT
Updated: 1d ago
📋 Project at a Glance
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What's this?A , built with Python open-source project in the Learning & Resources category, core strengths: artificial-intelligence/data-science
Who made it?Maintained by recommenders-team team, 21.9K⭐ on GitHub, #127 out of 3640 in Learning & Resources
Why does it exist?The recommenders-team team recognized that existing artificial-intelligence tools in Learning & Resources were hard to use. recommenders was designed to make data-science more accessible.
What can it do?Key use cases: deep-learning, jupyter-notebook, kubernetes
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README — the AI handles the rest.
🔗 github.com/recommenders-team/recommenders | 官网 https://recommenders-team.github.io/recommenders/intro.html
🔗 github.com/recommenders-team/recommenders | 官网 https://recommenders-team.github.io/recommenders/intro.html
Topics
aiartificial-intelligencedata-sciencedeep-learningjupyter-notebookkubernetesmachine-learningoperationalizationpythonrankingratingrecommendationrecommendation-algorithmrecommendation-enginerecommendation-systemrecommendertutorial