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MLAlgorithms

Simple, readable code examples of classic machine-learning methods, written to help you learn how they work.

New this week

What it does

This project collects short, clean versions of well-known machine-learning methods, written in Python. Examples include neural networks, random forests, k-means clustering, support vector machines and a basic form of reinforcement learning.

The code is meant to be easy to read rather than fast. Its author says it is aimed at people who want to understand the inner workings of these methods or write them from scratch.

Who it's for

Students and programmers learning how machine learning works under the hood.

Can I use it without coding?

Developers only. It's Python code you read and run. Some programming knowledge is needed. New to this? Start here.

Can I run it?

Cost
FreeNothing to pay or sign up for.
Computer
An ordinary computer is fine
Privacy
Runs on your own device: your data stays with you
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

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