Machine Learning

Catalog description

In classical programming, answers are obtained from rules and data. In machine learning, rules are obtained from data and answers. The widespread availability and sharing of data, and improvements in computing capacity, processing methods, and algorithms have given machine learning the power to deliver game-changing systems and technologies to organizations that compete on predictive, prescriptive, and/or autonomous analytics. In this course, we'll look at methods for using, tuning, and comparing machine learning algorithms, based on measures of performance, accuracy, and explainability. We'll also look at recent advances and trends in automated machine learning. Prerequisite(s): Data Acquisition and Management; Computational Statistics and Probability.