ECE 449 - Machine Learning

Spring 2022

TitleSectionCRNTypeHoursTimesDaysLocationInstructor
ONL0 -    

Course Description

This course covers principles and applications of machine learning. Main paradigms and techniques, including discriminative and generative methods, reinforcement learning: linear regression, logistic regression, support vector machines, deep nets, structured methods, dimensionality reduction, k-means, Gaussian mixtures, expectation maximization, Markov decision processes, and Q-learning. Application areas such as natural language and text understanding, speech recognition, computer vision, data mining, and adaptive computer systems, among others.

Credit Hours

3 or 4 hours

Prerequisites

Subject Area

  • Electrical and Computer Engineering