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ELE 290 - Machine Learning for Engineers

Department: Engineering, Electrical

Description: Introduction to machine learning and applications. Neural network (NN) models and structures. Training, validation and test data pre-processing and scaling. Universal approximation theorem. Error Backpropagation. Optimization and training algorithms. NN model utilization for design. Diversity and potential of engineering applications. Practical considerations of machine learning.

Credit Hours: 3

Prerequisites: MAT 149 Engineering Mathematics

This course has no upcoming offerings. Please contact the department if you have questions about when this will be offered.