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.
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This Course content is very good and has good real-time examples. However, the Instructor should add a few videos on SVD, Maximum dilation, and Shrinkage and Direction of Maximum Dilation.
Pros and cons. Sometimes it's hard to find in this course needed information to solve Assignments.\n\nBut you have to dig deeper from outside sources.
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.
Its a very good experience for me and it helps me to learn new topics and known new matters. Thank You Coursera.