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.
- 5 stars74.71%
- 4 stars19.74%
- 3 stars3.40%
- 2 stars1.14%
- 1 star0.99%
MATHEMATICS FOR MACHINE LEARNING: LINEAR ALGEBRA からの人気レビュー
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.
Great content and direction. Only negative is the sometimes frustrating experience with the Jupyter Notebooks: debugging what has gone wrong is very difficult, due to a lack of good error messages.
even though my code was right in the last assignment the grader kept getting timed out. it took 3 days to work and in the end the code was same. the course on the other hand was quite good and easy.
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.