Course Title
Machine Learning
Course Description
This course provides an introduction to the systematic study of algorithms and systems that improve their knowledge or performance with experience. A statistical approach that emphasizes concepts and the implementation of the methods is presented to make sense of large and complex data. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering. Prerequisites: MATH-180 Statistical Methods (or both MATH-108 Introduction to Statistics and BSAN-233 Data Driven Decision Making), MATH-201 Linear Algebra, and CSCI-181 Principles of Computer Science. 4 SH.
Course Types
Standard (STAND)
Semester Hours
4