Explore machine learning tools for signal processing, focusing on data compression and noise removal in this comprehensive meetup video. Dive into Principal Component Analysis (PCA) and discover how linear algebra can be applied to these and other applications. Learn from Sara, an experienced electrical engineer and Ph.D. holder, as she covers topics such as data extraction, clustering analysis, deep learning, and alternative techniques when PCA falls short. Gain valuable insights into the fundamentals of machine learning and its practical applications in signal processing through this informative presentation, complete with a Q&A session to address your specific queries.
Machine Learning for Signal Processing - Data Compression and Denoising
Overview
Syllabus
– Introduction
– Data extraction
– Signal processing
– How PCA works
– Linear algebra
– Clustering analysis
– When PCA doesnt work
– Other techniques
– Deep learning
– QnA
Taught by
Data Science Dojo
