Part 5: Singular Values and Singular Vectors

Name: Part 5: Singular Values and Singular Vectors
Uploaded: 2020-05-05T12:42:04Z
Duration: 13 min 15 s
Description: Description Data matrices in machine learning are not square, so they require a step beyond eigenvalues: The Singular Value Decomposition (SVD) expresses every matrix by its singular values and vectors. Slides Used in this Video: Slides 25 through 30 Instructor: Gilbert Strang

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Part 6: Finding the Nullspace: Solving Ax = 0 by Elimination

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Description

Data matrices in machine learning are not square, so they require a step beyond eigenvalues: The Singular Value Decomposition (SVD) expresses every matrix by its singular values and vectors.

Slides Used in this Video: Slides 25 through 30

Instructor: Gilbert Strang