6.867 Machine Learning (2012 Fall)

From Course 6.867

Jump to: navigation, search
  • All the announcements and handouts area on Piazza, follow the link below.
  • The recitation times and places are on Piazza; they have changed from what is in the catalog.

Useful Links

  • Piazza is our course discussion system and mailing list; we will also use it for distributing handouts and announcements. Please subscribe to 6.867 on Piazza if you haven't already, otherwise you may miss announcements. You will also miss out on all the useful discussion on the site.
  • E-mail staff at 6867-staff-2012@lists.csail.mit.edu

Project

Programming Resources

Mathematics

  • Matrix cookbook pdf
  • Lagrange multipliers [1]
  • A Tutorial on E-M [2]

Books

Course Information

  • This introductory course on machine learning will give 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.
  • Prerequisites: (6.041 or 18.05) and 18.06; 6.034 is helpful
  • Lectures: Tue. and Thu. 9:30AM - 11AM in 54-100
Personal tools