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
Matrix Methods
Instructor: Daniel Boley
Access provided by University of Colombo School of Computing
13,471 already enrolled
Gain insight into a topic and learn the fundamentals.
4.1
(248 reviews)
Intermediate level
Some related experience required
6 hours to complete
Flexible schedule
Learn at your own pace
Skills you'll gain
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Assessments
18 assignments
Taught in English
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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
Instructor
Instructor ratings
3.8 (54 ratings)Offered by
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4.1
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JD
5
Reviewed on May 31, 2020
Very good course, the questions are really challenging...
DB
4
Reviewed on Nov 17, 2019
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.
LF
5
Reviewed on Dec 26, 2020
Succinct, informative, efficient. Thank you, Dr. Boley.
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