Learner Reviews & Feedback for Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors by Johns Hopkins University
4.9
stars
21 ratings
About the Course
This course is the second course in the Linear Algebra Specialization. In this course, we continue to develop the techniques and theory to study matrices as special linear transformations (functions) on vectors. In particular, we develop techniques to manipulate matrices algebraically. This will allow us to better analyze and solve systems of linear equations. Furthermore, the definitions and theorems presented in the course allow use to identify the properties of an invertible matrix, identify relevant subspaces in R^n,
We then focus on the geometry of the matrix transformation by studying the eigenvalues and eigenvectors of matrices. These numbers are useful for both pure and applied concepts in mathematics, data science, machine learning, artificial intelligence, and dynamical systems. We will see an application of Markov Chains and the Google PageRank Algorithm at the end of the course....
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1 - 2 of 2 Reviews for Linear Algebra: Matrix Algebra, Determinants, & Eigenvectors
By 2303A 5
•
Apr 12, 2024
good guidance
By Dawit Y
•
Dec 27, 2023
It helps me to advance my knowledge and the way of teaching is just to the point, that's what i was looking for.
I would say it would be great if their are more examples included.