Course Description:
Provides systematic introduction to machine learning, covering basic theoretical as well as practical aspects of the use of machine learning methods. Topics include learning theory, learning methods, recent learning models, etc. Application examples include multimedia information retrieval, text recognition, computer vision, etc.Prerequisite:
- C or higher in CS 3358: Data Structures
Course Objectives:
- Introduces fundamental principles of machine learning and their implications for the basic problems of modeling and inference.
- Emphasis is on algorithms and models useful in a broad range of applications & understanding the underlying assumptions, weaknesses & strengths of each approach.
- Students are to become familiar with the arsenal of modern machine learning so that, as practioners, they can judge when a particular tool is appropriate & how it can be adapted to the problem at hand.
Course Notes:
None.
Section Info:
Course deleted effective Fall 2018. Replaced by CS 4347.