Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
Matrix MethodsUniversity of Minnesota
About this Course
- 5 stars55.45%
- 4 stars20%
- 3 stars9.54%
- 2 stars7.27%
- 1 star7.72%
TOP REVIEWS FROM MATRIX METHODS
This Course content is very good and has good real-time examples. However, the Instructor should add a few videos on SVD, Maximum dilation, and Shrinkage and Direction of Maximum Dilation.
It was a great opportunity to know more abut matrices and their characteristics
Very good course, the questions are really challenging...
Pros and cons.
Sometimes it's hard to find in this course needed information to solve Assignments.
But you have to dig deeper from outside sources.
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