Linear Algebra

Singular Value Decomposition (SVD)

First heard from f1tenth.


Also mentioned from this video 10:30 for Zero-shot Learning.

In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any matrix.

Be familiar with your eigenvalues

This is a prerequisite. I still forget the point of eigenvalues.


Look at

Singular value