Algorithms for Inference

Rendering of two robots playing a game.

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)

MIT Course Number

6.438

As Taught In

Fall 2014

Level

Graduate

Cite This Course

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.

Devavrat Shah. 6.438 Algorithms for Inference, Fall 2014. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu (Accessed). License: Creative Commons BY-NC-SA


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