Singular Value Decomposition Example

Singular Value Decomposition (SVD) is a fundamental technique in linear algebra with applications in various fields such as signal processing, statistics, machine learning, and data analysis. It is a method to decompose a matrix into three simpler matrices, revealing its underlying structure.

Singular Value Decomposition (SVD) is a factorization method used in linear algebra to decompose a matrix into three separate matrices:
A=UΣV^T