Machine Learning

Image of robotic mannequin, 'Manny', constructed at Pacific Northwest Laboratory.

Robotic mannequin, "Manny", constructed at Pacific Northwest Laboratory. (Image is taken from Department of Energy's Digital Archive.)

Instructor(s)

MIT Course Number

6.867

As Taught In

Fall 2006

Level

Graduate

Translated Versions

ภาษาเขียน

Cite This Course

Course Features

Course Description

6.867 is an introductory course on machine learning which gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as classification and linear regression and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work. The underlying theme in the course is statistical inference as it provides the foundation for most of the methods covered.

Archived Versions

Singh, Rohit, Tommi Jaakkola, and Ali Mohammad. 6.867 Machine Learning, Fall 2006. (MIT OpenCourseWare: Massachusetts Institute of Technology), http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-867-machine-learning-fall-2006 (Accessed). License: Creative Commons BY-NC-SA


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