ECE 47301 - Machine Learning

Prerequisite(s): (ENGR 15100 FOR LEVEL UG WITH MIN. GRADE OF D- OR ECE 15200 FOR LEVEL UG WITH MIN. GRADE OF D-) AND MA 26100 FOR LEVEL UG WITH MIN. GRADE OF D- AND MA 26500 FOR LEVEL UG WITH MIN. GRADE OF D- AND ECE 30200 FOR LEVEL UG WITH MIN. GRADE OF D-

Credit Hours: 3.00. This course introduces the fundamental concepts and algorithms of machine learning (ML) with their implementations and applications to practical problems consisting of modeling and prediction. Students will gain knowledge on the formulation of learning representation, over-fitting, generalization, clustering, classification, regression, and probabilistic modeling. Topics include linear regression, supervised and unsupervised learning, dimensionality reduction, Naïve Bayes, feedforward neural networks, deep convolutional neural networks, and the state-of-the-art machine learning libraries. (Please see the attached syllabus for detailed information)

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