SVD - Singular Value Decomposition

Every real matrix have a singular value decomposition which is different than eigenvalue decomposition because it's only for square matrices.

$$A = UDV^T$$

$U, V$both are orthogonal and $D$is diagonal matrix (not necessarily square)