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 stars74.65%
- 4 stars19.77%
- 3 stars3.40%
- 2 stars1.14%
- 1 star1.02%
TOP REVIEWS FROM MATHEMATICS FOR MACHINE LEARNING: LINEAR ALGEBRA
Excellent course on the relevant parts of linear algebra for CS. Both instructors are great fun to watch and the assignments use up-to-date Python programming and Jupyter notebooks. Well done !!!
Good course with nice lecturer.
Some topics should be explain more in detail and have some further reading / exercise for practicing.
For overall, this course is worth the time and money spend.
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 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.
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