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Recommenders

Worked examples and best practices for building recommendation systems, like "you might also like" features.

What it does

Recommendation systems suggest products, films or articles based on what people liked before. This project collects step-by-step notebooks on preparing data, building models, measuring results and putting them into use.

It also includes a Python library with ready-made versions of many methods. It is part of the Linux Foundation's AI & Data group.

Who it's for

Data scientists, students and developers learning to build recommendation features.

Can I use it without coding?

Developers only. Uses Python notebooks and needs programming. New to this? Start here.

Can I run it?

Cost
FreeNothing to pay or sign up for.
Runs on
Linux, Windows, Mac
Computer
An ordinary computer is fine
API key
Not needed

Try it

Using Claude Code, Cursor or another AI coding assistant? Paste the prompt and it will walk you through the setup.New to this?

Before you install

  • Only download from the official GitHub page. Copies with similar names exist for many popular projects.
  • License (MIT): Very permissive: free to use, change and share, including for business.
  • More on staying safe