CS 381 - Machine Learning

Institution:

DigiPen Institute of Technology

Subject:

Description:

Prerequisite(s): CS 280 This course deals with constructing computer programs that automatically improve with experience. Observed events are used to inductively construct decision trees, which can be used by computer-controlled game characters to change behaviors. Students will explore concept learning, partial ordering, reinforcement learning, conditional probability, Bayesian learning, the evaluation of hypotheses and instance-based learning. Types of neural networks examined include perceptrons, backpropagation, radial basis functions, and adaptive resonance theory. We demonstrate the effectiveness of genetic algorithms and show the power of a neuro-genetic approach. The class concludes by looking at inductive analytical learning.

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.digipen.edu

Phone Number:

(425) 558-0299

Calendar System:

Semester

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