University of Delaware 3 credits ELEG
Matrix and tensor methods underlie much of modern signal processing, machine learning, and data science. This course provides an overview of powerful techniques and fundamental theory for matrix and tensor methods in these contexts. The goal is for students to become fluent in applying these techniques (through hands-on experience deriving and implementing algorithms) and to learn how to use these techniques wisely (by looking “under the hood” at the underlying theory). Restrictions: Knowledge of linear algebra, vector calculus, and probability.
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