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 Pontificia Universidad Católica del Perú
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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 10, 2021
It was a great opportunity to know more abut matrices and their characteristics
Reviewed on Aug 16, 2020
Thank you so much for giving me this opportunity to learn about matrix methods. This is helpful for my career and it is useful to all the beginners.
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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