Mathematics, Linear Algebra, Machine Learning, Data Science.
Singular Value Decomposition (SVD) is a fundamental matrix factorization technique in linear algebra. It is used to decompose a matrix into three simpler matrices. The SVD theorem can be stated as following : where : U is an m×m orthogonal matrix whose columns are the left singular vectors of A. Σ