Supervised and unsupervised machine learning methods for regression, classification, clustering, and time series modeling. Methods of fitting models. The problem of overfitting and techniques for addressing it. Deep learning and neural network models. Processes for how to refine/ implement/ test applications of machine/deep learning algorithms.
PREREQUISITE(S):
ELEC 278 or CISC 235, ELEC 326 or permission of the instructor.