In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works.
About this Course
Skills you will gain
- 5 stars74.69%
- 4 stars19.74%
- 3 stars3.40%
- 2 stars1.14%
- 1 star1%
TOP REVIEWS FROM MATHEMATICS FOR MACHINE LEARNING: LINEAR ALGEBRA
The content of the course is very relevant, and the instructors are really fun and helpful.My only suggestion is to upload revisions for each assessment, so we can understand what we are doing wrong.
The instruction was good throughout, but I would urge fellow students to take the time to work through the problems as suggested. Also, the eigen- stuff is quite tricky and can fool you. Be careful.
Excellent course!! The Mathematics for Machine Leaning : Linear Algebra offered by the Imperial College of London it's a good step into building a strong foundation in the field of Linear Algebra.
Great way to learn about applied Linear Algebra. Should be fairly easy if you have any background with linear algebra, but looks at concepts through the scope of geometric application, which is fresh.
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