MATH 398 - Machine Learning

Machine Learning is at the core of advances and new applications in science: autonomous vehicles, speech recognition/translation, traffic/weather alerts, fraud detection, recommender systems, vaccine development, genomics, and many more. This course provides in-depth background for a variety of machine learning, data mining, and statistical pattern recognition techniques.

Prerequisites
MATH 251 Methods of Data Analysis or COMP 255 Artificial Intelligence/Machine Learning or permission of instructor

Credits 4

Notes
From time to time, departments design a new course to be offered either on a one-time basis or an experimental basis before deciding whether to make it a regular part of the curriculum. Last offered Spring 2023.

Area
Math and Computer Science

Compass Attributes
Quantitative Analysis