ENGR 347 - Machine Learning

3 hours
A project-based course exploring the theory and application of machine learning. Development of machine learning solutions using Python, Sci-kit Learn, TensorFlow, and Keras. Introduction to linear and logistic regression, binary classification, support vector machines, decision trees, ensemble methods, artificial neural networks, and convolutional neural networks. Every spring Prerequisite(s): ENGR 107 or COMP 150; MATH 241 or MATH 351. UG