Learn optimization

🚧 This collection is a work in progress. Check back later for new notebooks!

This collection of marimo notebooks teaches you the basics of mathematical optimization.

After working through these notebooks, you'll understand how to create and solve optimization problems using the Python library CVXPY, as well as how to apply what you've learned to real-world problems such as portfolio allocation in finance, resource allocation, and more.

SpaceX solves convex optimization problems onboard to land its rockets, using CVXGEN, a code generator for quadratic programming developed at Stephen Boyd’s Stanford lab. Photo by SpaceX, licensed CC BY-NC 2.0.

Running notebooks. To run a notebook locally, use

uvx marimo edit <URL>

For example, run the least-squares tutorial with

uvx marimo edit https://github.com/marimo-team/learn/blob/main/optimization/01_least_squares.py

You can also open notebooks in our online playground by appending marimo.app/ to a notebook's URL: marimo.app/github.com/marimo-team/learn/blob/main/optimization/01_least_squares.py.