Machine Learning

Catalog description

This course offers a thorough introduction to machine learning methods. We will learn how the machine learning methods can help us explore the data and build accurate predictive models. The following concepts will be covered: regression, classification, model selection, tree-based methods, random forest, boosting, support vector machines, neural network, deep learning and unsupervised learning (principal component analysis, clustering). Prerequisite(s): Undergraduate level STT 3600 Minimum Grade of D or Undergraduate level STT 3700 Minimum Grade of D Course Level: Undergraduate Schedule Type(s): Lecture Grade Mode: Standard Term(s) Offered: Fall, Spring, Summer