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
Gain insight into a topic and learn the fundamentals.
4.1
(238 reviews)
Intermediate level
Some related experience required
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
Details to know
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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
Recommended if you're interested in Math and Logic
Stanford University
Coursera Project Network
Vanderbilt University
Johns Hopkins University
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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...
M
5
Reviewed on Apr 20, 2020
Its a very good experience for me and it helps me to learn new topics and known new matters.
LF
5
Reviewed on Dec 26, 2020
Succinct, informative, efficient. Thank you, Dr. Boley.
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