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  1. Linear Algebra
  2. Matrix Decomposition

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=UDVTA = UDV^TA=UDVT

U,VU, VU,Vboth are orthogonal and DDDis diagonal matrix (not necessarily square)

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Last updated 3 years ago