The material in this course constitutes a common foundation for work in machine learning, signal processing, artificial intelligence, computer vision, control, and communication. (Image courtesy of Nebraska Oddfish on Flickr. CC BY-NC-SA 2.0.)
Instructor(s)
Prof. Devavrat Shah
MIT Course Number
6.438
As Taught In
Fall 2014
Level
Graduate
Course Description
Course Features
Course Description
This is a graduate-level introduction to the principles of statistical inference with probabilistic models defined using graphical representations. The material in this course constitutes a common foundation for work in machine learning, signal processing, artificial intelligence, computer vision, control, and communication. Ultimately, the subject is about teaching you contemporary approaches to, and perspectives on, problems of statistical inference.