Все публикации

0:09:11

Lecture4c: Coordinates

0:16:33

Lecture 10e: Why do matrices have singular value decompositions?

0:13:42

Lecture 10a: Eigenvectors of symmetric matrices

0:11:01

Lecture 10c: How to compute singular value decomposition

0:12:30

Lecture 10b: Singular value decomposition

0:05:00

Lecture 10d: How to use singular value decomposition

0:13:02

Lecture 9c: Algebraic and geometric multiplicity

0:08:58

Lecture 9b: Eigenbases

0:15:24

Lecture 9d: Algebraic and geometric multiplicity: proofs

0:06:47

Lecture 9a: Diagonalization

0:06:10

Lecture 8b: Computing eigenvalues and eigenvectors

0:07:56

Lecture 8c: Formulas for powers of matrices

0:18:23

Lecture 7c: Formulas for determinants

0:18:37

Lecture 7b: Geometry of determinants

0:14:10

Lecture 8a: Introduction to eigenvalues and eigenvectors

0:15:35

Lecture 6b: The method of least squares

0:05:05

Lecture 6c: Least squares and data fitting

0:13:42

Lecture 7a: Properties of determinants

0:13:04

Lecture 6a: QR decomposition

0:07:03

Lecture 5c: Orthogonal projection

0:14:23

Lecture 5d: The Gram-Schmidt algorithm

0:11:11

Lecture 5b: Orthonormal bases

0:09:48

Lecture 5a: Dot products

0:09:03

Lecture 4b: Dimension