Units: 4 Terms Offered: SpDistribution-free and probabilistic methods for supervised classification and regression; learning algorithms; optimization techniques; feature-space transformations; parametric and nonparametric methods; Bayes decision theory; artificial neural networks. Recommended Preparation: knowledge of Python at the level of EE 541 (A Computational Introduction to Deep Learning); knowledge of multivariate calculus. Corequisite:EE 503 and EE 510 Instruction Mode: Lecture, Discussion Grading Option: Letter
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