Overview
Learn about singular value decomposition (SVD), a powerful matrix technique, and its application to image compression in this 29-minute video. Explore how to express a matrix as a product of two rotation matrices and one scaling matrix. Dive into transformations, linear transformations, and dimensionality reduction. Discover practical applications of SVD in image compression. Access additional resources, including a GitHub repository and related videos on principal component analysis and matrix factorization for Netflix recommendations. Gain valuable insights into this essential mathematical concept and its real-world applications in data science and machine learning.
Syllabus
Introduction:
Transformations:
A puzzle:
A harder puzzle:
Linear transformations:
Dimensionality reduction:
Image compression:
Taught by
Serrano.Academy