Advanced Linear Algebra - Lecture 30: Introduction to Positive (Semi)Definite Matrices

We introduce positive definite and positive semidefinite matrices, and present a theorem that characterizes them in several different ways.

Please leave a comment below if you have any questions, comments, or corrections.

Timestamps:
00:00 - Introduction
00:38 - Definition
01:52 - 2x2 example
06:09 - Characterization theorem
09:04 - Proof of theorem
18:22 - 2x2 example again

[Kyle-qrpu]

The best intuitive and organized explanation. Many thanks

[LayKxD]

I love you. Taking optimization theory and needed a quick review of linear algebra. This is detailed and helped me

[hr]

@10:48 minor typo, since v is non zero by definition of eigen vector, norm of v is always bigger than zero.