CSCI 4100 - Machine and Computational Learning

Institution:

Roberts Wesleyan University

Subject:

Description:

Introduction to the theory, algorithms, and applications of automated learning (supervised, reinforcement, and unsupervised), how much information and computation are needed to learn a task, and how to accomplish it. Emphasis will be given to unifying approaches coming from statistics, function approximation, optimization and pattern recognition. Topics include: Decision Trees, Neural Networks, RBF's, Bayesian Learning, PAC Learning, Support Vector Machines, Gaussian processes, Hidden Markov Models. Prerequisites/Corequisites: Prerequisites: familiarity with probability, linear algebra, and calculus. When Offered: Offered on availability of instructor. Credit Hours: 4

Credits:

4.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

WWW.Roberts.edu

Phone Number:

(585) 594-6000

Regional Accreditation:

Middle States Association of Colleges and Schools

Calendar System:

Semester

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