Course Highlights
6.867 is offered under the department's "Artificial Intelligence and Applications" concentration. The site offers a full set of
lecture notes,
homework assignments, in addition to other materials used by students in the course.
Course Description
6.867 is an introductory course on machine learning which provides an overview of many techniques and algorithms in machine learning, beginning with topics such as simple perceptrons and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, and Bayesian networks. The course gives the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how and why they work. The underlying theme in the course is statistical inference as this provides the foundation for most of the methods covered.