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HomeMIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018Lecture 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
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Lecture 1: The Column Space of A Contains All Vectors Ax
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Lecture 2: Multiplying and Factoring Matrices
Description
In this first lecture, Professor Strang introduces the linear algebra principles critical for understanding the content of the course. In particular, matrix-vector multiplication \(Ax\) and the column space of a matrix and the rank.
SummaryIndependent columns = basis for the column space
Rank = number of independent columns
\(A = CR\) leads to: Row rank equals column rank
Related section in textbook: I.1
Instructor: Prof. Gilbert Strang
