This video presents an overview of the singular value decomposition (SVD), which is one of the most widely used algorithms for data processing, reduced-order modeling, and high-dimensional statistics.
These lectures follow Chapter 1 from:
"Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Brunton and Kutz
Amazon: https://www.amazon.com/Data-Driven-Science-Engineering-Learning-Dynamical/dp/1108422098/
Book Website: http://databookuw.com
Chapters available at: http://databookuw.com/databook.pdf
Brunton Website: http://eigensteve.com
This video was produced at the University of Washington