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# 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](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,
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
```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).
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