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Homemade Machine Learning

Explains popular machine learning methods with simple code written from scratch and interactive demos.

What it does

This project teaches how common machine learning methods work by building them from scratch in Python, instead of using ready-made libraries. Each method comes with an explanation of the maths behind it.

Topics include predicting numbers, sorting things into groups, finding clusters and simple neural networks. Each one has an interactive notebook where you can change the data and settings and see the results, for example predicting a country's happiness score from its economy.

Who it's for

Students and programmers who want to understand what's going on inside machine learning.

Can I use it without coding?

Developers only. You can view the demos online, but changing them means working with Python notebooks. New to this? Start here.

Can I run it?

Cost
FreeNothing to pay or sign up for.
Runs on
Web browser
Computer
An ordinary computer is fine
API key
Not needed

Try it

  1. Open any demo notebook in your browser through the Binder link, with nothing to install.
  2. Change the training data or settings and see the results and charts update.

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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