The singular value decomposition

Every matrix of every shape is a rotation, a scaling along perpendicular axes and another rotation; the singular values are the scalings, and they carry the rank, the four subspaces, the conditioning and the best low-rank approximation.

About 30 minutes7 activities Paper packet