gpeyre/numerical-tours

What it is

A collection of complete, runnable experiments in mathematical data science, created by Gabriel Peyré and contributors. Every example includes its implementation code directly in the notebooks, so you can read the method and run it yourself.

What it covers

The main collection spans six areas: imaging, optimization, optimal transport, machine learning, signals, and geometry.

How it's organized

• Python notebooks are the recommended starting point (see python/README.md).
• The matlab, julia, and r folders hold earlier language-specific editions.
• Browser-friendly content is at numerical-tours.com.
• Code lives on two branches: the website source on gh-pages, and Python content on master.
• For installation, verification, and exporting the website, consult maintenance/README.md.

How to use it

Open the Python notebooks or browse the website, then run the experiments directly from the notebooks. The maintenance guide covers setup and checks.