DATA412

This course will cover some of the more advanced topics in Linear Algebra beyond what is covered in traditional undergraduate courses. The focus will be on exploring theory which is used in real Data Science applications, including matrix factorization, low-rank matrix approximations, kernel methods, graph theory, and optimization. Some special modern topics will be covered such as Compressed Sensing, Data Clustering, and Frame Theory. The theory will be complemented with illustrative applications.

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