Pattern Recognition and Analysis OpenCourseWare: MIT's Free Graduate Study Course on Pattern Recognition in Numerical Data

Published Jan 02, 2009

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This Massachusetts Institute of Technology (MIT) OpenCourseWare class, 'Pattern Recognition and Analysis,' deals with finding patterns in numbers. The free course provides brief reviews on necessary mathematical concepts, covers pattern recognition theory and presents a wide variety of pattern recognition applications, such as speech recognition and user modeling. Though students of any discipline are encouraged to participate in this class (provided they have basic MatLab experience), the course is designed for engineering and science students.

Pattern Recognition and Analysis: Course Specifics

Degree Level Free Audio Video Downloads
Graduate Yes No No Yes

Lectures/Notes Study Materials Tests/Quizzes
Yes Yes No

Pattern Recognition and Analysis: Course Description

Pattern recognition is at work in us and in the world at large. Our brains pick up on patterns in nature unconsciously, and fingerprint identification limits access to restricted areas or items using special pattern recognition software. This course covers the mathematics that make such pattern recognition and analysis possible. In addition to an introduction on pattern recognition, feature detection and classification, you will learn about random vectors, probability theory, linear dynamical systems, linear and quadratic discriminants, Bayesian networking, decision theory, non-parametric classification, machine and human learning and much more. These topics are of particular interest to science and engineering students. The MIT media lab faculty and staff teach this course and organize the on-campus course into a series of lectures with project presentations at the end of the course.

This OpenCourseWare offers online access to assignments, slide presentations about the textbook, a MatLab tutorial, project examples and special assignment notes. The course textbook and the MatLab program are not free with the OpenCourseWare and must be purchased separately. If you're interested in taking this free course, visit the pattern analysis and recognition page.

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