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
Sponsored by Louisiana Workforce Commission
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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 Dec 26, 2020
Succinct, informative, efficient. Thank you, Dr. Boley.
Reviewed on Apr 20, 2020
Its a very good experience for me and it helps me to learn new topics and known new matters.
Recommended if you're interested in Math and Logic
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