TDSM 8.21
From The Data Science Design Manual Wikia
What is singular value decomposition?
In linear algebra, the singular-value decomposition (SVD) is a factorization of a real or complex matrix. If we have matrix M the SVD is in a form of [math] M=UDV^T [/math] where D is diagonal (weighted identity matrix).
What is a singular value?
Each diagonal entries of D is called a singular value of M.
what is a singular vector?
The columns of U and the columns of V are called the left-singular vectors and right-singular vectors of M , respectively
