Computer Science 235 - Applications of Machine Learning

This course provides a practical and conceptual introduction to machine learning. Through programming projects and work with real-world data, we will study the motivations behind common machine learning algorithms, and the properties that determine whether or not they will work well for a particular task. We will also study practical applications of these algorithms to problems in areas such as speech, language, social sciences, and biology. Topics may include: supervised learning, classification, regression, clustering, decision trees, support vector machines, Naïve Bayes, neural networks and reinforcement learning.

Prereq: COMSC-205.