Python Symbolic Regression - Physics Informed Machine Learning

Explore the concept of Python Symbolic Regression (PySR) in this 16-minute video lecture from the University of Washington. Delve into the fundamentals of symbolic regression, its applications in physics-informed machine learning, and the high-level algorithm behind genetic programming. Learn about the history of symbolic discovery and its significance in various fields. Discover the advantages of using PySR, its features, and benchmarks. Gain insights into the code structure and understand why symbolic regression is a powerful tool for data-driven modeling and scientific discovery. The lecture concludes with a discussion on the potential impact and future directions of this approach in machine learning and scientific research.

Intro
What is Symbolic Regression?
High-Level Algorithm/ Genetic Programming Overview
// Crossover and Mutation
History of Symbolic Discovery/ Background: Symbolic Discovery
// Symbolic Discovery Case Study
// Case Study: Control Laws
Why PySR
// PySR: Features
// PySR: Benchmarks
// PySR: Code Structure
Why Symbolic Regression/ Potential Outro
Outro