Additionally, students must always refer to course syllabus for the most up to date information. Introduces the fundamentals of linear algebra in the context of computer science applications. Includes ...

Supplementary material may be drawn from the following two texts: Matrix Computations by Gene Golub and Charles van Loan, Johns Hopkins 2013 (third or fourth editions) Iterative Methods for Sparse ...

Computations that involve matrix algorithms are happening everywhere in the world at every moment in time, whether these be embedded in the training of neural networks in data science, in computer ...

This bridge course has a very practical curriculum, which covers the fundamentals of linear algebra as they are used in applied statistics courses. Some of the topics include, but are not limited to, ...