This bootcamp explores the wide world of mathematical optimization, specifically for applications in machine learning, control theory, and inverse problems. This closely follows the textbook "Optimization: A Bootcamp for Machine Learning, Inverse Problems, and Control" (https://www.amazon.com/Optimization-Bootcamp-Machine-Learning-Problems/dp/1009755862)
Curated by: Steve Brunton (44 videos)
Here we provide a high-level overview of some of the applications of optimization in modern machine learning, physics, and engineering. Applications include physics informed machine learning, control theory, inverse design, and the digital twin. This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company. %%% CHAPTERS %%% 00:00 Intro 01:50 Machine Learning 05:06 Physics Informed Machine Learning 10:00 Control Theory 12:45 Inverse & Inverse Design Problems 21:52 The Digital Twin 24:15 Outro