Description
Machine Learning
Machine learning is the process of making predictions and decisions from data without being explicitly programmed. Topics include a variety of supervised learning methods. Ensemble approaches are used to combine independent models efficiently. Unsupervised and semi-supervised methods demonstrate the power of learning from data without an explicit training goal.

Prerequisite: (COMP 231 or COMP 271) and (STAT 103 or STAT 203 or ISSCM 241 or PSYC 304 or instructor permission).

Outcomes: Students in this course will learn how to apply sophisticated algorithms to large data sets to make inferences for prediction or decision making.
Details
Grading Basis
Graded
Units
3
Component
Lecture - Required
Offering
Course
COMP 379
Academic Group
College of Arts and Sciences
Academic Organization
Computer Science
Enrollment Requirements
Prerequisites: At least C- in (COMP 231 or COMP 271) and (STAT 103 or STAT 203 or ISSCM 241 or PSYC 304 or instructor permission)