ECE 53910 - Neural Networks: From Theory To Practice

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

Credit Hours: 3.00. This course introduces artificial neural networks (ANNs), which are a subset of machine learning and artificial intelligence. Topics include the ANN mathematics and linear algebra used to model input and output data, optimization algorithms for weight training, the supervised learning process, regression and classification problems, and an introduction to deep neural networks, including their applications in computer vision and natural language processing. Assignments include programming ANNs algorithmically in MATLAB and from built-in machine learning libraries in Python. Permission of instructor required.

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