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 Methods

Instructor: Daniel Boley
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There are 5 modules in this course
What's included
3 videos2 readings3 assignments
What's included
3 videos2 readings3 assignments
What's included
4 videos3 readings4 assignments
What's included
4 videos2 readings5 assignments
What's included
2 readings3 assignments
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Reviewed on May 31, 2020
Very good course, the questions are really challenging...
Reviewed on Mar 16, 2020
Really its very informative and basic material provided. I enjoyed and learn a lot
Reviewed on Aug 31, 2022
This has been a helpful course. I had the chance to learn about practical applications of matrices.
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