Lecture 2: Multiplying and Factoring Matrices

Автор: MIT OpenCourseWare

Загружено: 2019-05-16

Просмотров: 171558

Описание:

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018
Instructor: Gilbert Strang
View the complete course: https://ocw.mit.edu/18-065S18
YouTube Playlist: • MIT 18.065 Matrix Methods in Data Analysis...

Multiplying and factoring matrices are the topics of this lecture. Professor Strang reviews multiplying columns by rows: AB = sum of rank one matrices. He also introduces the five most important factorizations.

License: Creative Commons BY-NC-SA
More information at https://ocw.mit.edu/terms
More courses at https://ocw.mit.edu

Lecture 2: Multiplying and Factoring Matrices

Доступные форматы для скачивания:

Скачать видео mp4

Информация по загрузке:

Скачать аудио mp3

Похожие видео

3. Orthonormal Columns in Q Give Q'Q = I

3. Orthonormal Columns in Q Give Q'Q = I

6. Singular Value Decomposition (SVD)

6. Singular Value Decomposition (SVD)

Dear linear algebra students, This is what matrices (and matrix manipulation) really look like

Dear linear algebra students, This is what matrices (and matrix manipulation) really look like

Математики открывают странную новую бесконечность

Математики открывают странную новую бесконечность

4. Eigenvalues and Eigenvectors

4. Eigenvalues and Eigenvectors

Lecture 1: The Column Space of A Contains All Vectors Ax

Lecture 1: The Column Space of A Contains All Vectors Ax

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018

MIT Learn Differential Equations

MIT Learn Differential Equations

17. Orthogonal Matrices and Gram-Schmidt

17. Orthogonal Matrices and Gram-Schmidt

MIT 6.S191: Reinforcement Learning

MIT 6.S191: Reinforcement Learning

Lecture 8: Norms of Vectors and Matrices

Lecture 8: Norms of Vectors and Matrices

MIT Introduction to Deep Learning | 6.S191

MIT Introduction to Deep Learning | 6.S191

2025 MIT Integration Bee - Finals

2025 MIT Integration Bee - Finals

12. Computing Eigenvalues and Singular Values

12. Computing Eigenvalues and Singular Values

Gambits Gone Wrong! | Tricks & Traps Speedrun Episode 32

Gambits Gone Wrong! | Tricks & Traps Speedrun Episode 32

1. The Geometry of Linear Equations

1. The Geometry of Linear Equations

The Big Problem With Solar Power

The Big Problem With Solar Power

Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra

Eigenvectors and eigenvalues | Chapter 14, Essence of linear algebra

29. Singular Value Decomposition

29. Singular Value Decomposition

Lecture 11: Minimizing ‖x‖ Subject to Ax = b

Lecture 11: Minimizing ‖x‖ Subject to Ax = b