optimization/README.md

metadata

title: Learn Optimization
description: >
  Learn the basics of convex optimization using Python, and see how to apply
  these ideas to vehicle control, portfolio allocation in finance, and other
  areas.

You can open and run these notebooks in molab, marimo's free hosted notebook platform.

After working through these notebooks, you'll understand how to create and solve optimization problems using Python's CVXPY library, as well as how to apply what you've learned to real-world problems.

Notebooks

• Least Squares
• Linear Program
• Minimal Fuel Optimal Control
• Quadratic Program
• Portfolio Optimization
• Convex Optimization
• Semidefinite Program

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.

Contributors

Thanks to our notebook authors:

• Akshay Agrawal