Sparsity and Compression
Explore the concepts of sparsity and compression in this comprehensive 4.5-hour video series. Delve into the vastness of image space, understand the fundamentals of compressed sensing, and learn how to beat the Nyquist sampling theorem. Discover the power of the L1 norm in robust regression and sparse representation for classification. Investigate advanced topics such as Robust Principal Component Analysis (RPCA) and sparse sensor placement optimization. Gain practical skills using Python and MATLAB to implement underdetermined systems, compressed sensing, and robust regression techniques. Examine the importance of parsimonious models and explore PySINDy, a Python library for model discovery. Master the art of creating simple yet effective models in data analysis and signal processing.