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.
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The techniques and tools covered in Mathematics for Machine Learning: Linear Algebra are most similar to the requirements found in Data Scientist job advertisements.
Mathematics for Machine Learning: Linear Algebra is a part of two structured learning paths.
Mathematics for Machine Learning
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