CS3332 Applied Machine Learning

Survey of machine-learning techniques of artificial intelligence with a particular focus on military applications.  Topics include types of machine learning, training and testing of machine learning, data preparation, decision trees, Bayesian reasoning, linear models, neural networks, case-based reasoning, and reinforcement learning.  Each method will be related to important military and government applications.  This course is intended for students who are not computer-science majors.

Prerequisite

CS3331, Basics of Applied Artificial Intelligence

Lecture Hours

4

Lab Hours

0

Quarter Offered

  • As Required

Outcomes

  1. Identify and distinguish the major methods of machine learning. -- Be able to prepare data for effective use of machine-learning methods. -- Be able to run machine-learning methods on a standard tool. -- Be able to interpret output of machine-learning methods, and draw valid conclusions from it. -- Understand the major terms used to describe machine learning. -- Be able to use machine-learning tools. -- Be able to draw conclusions from results of machine learning.