optimization/README.md

# Learn optimization

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

After working through these notebooks, you'll understand how to create
and solve optimization problems using the Python library
[CVXPY](https://github.com/cvxpy/cvxpy), as well as how to apply what you've
learned to real-world problems such as portfolio allocation in finance,
control of vehicles, and more.

![SpaceX](https://www.debugmind.com/wp-content/uploads/2020/01/spacex-1.jpg)

_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

```bash
uvx marimo edit <URL>
```

For example, run the least-squares tutorial with

```bash
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](https://marimo.app/https://github.com/marimo-team/learn/blob/main/optimization/01_least_squares.py).

**Thanks to all our notebook authors!**

* [Akshay Agrawal](https://github.com/akshayka)