Courses:

Engineering and Applied Sciences >> Human-Computer Interaction


For Course Instructors

  • Advertise your course for free
  • Feature your course listing
  • Create course discussion group
  • Link to your course page
  • Increase student enrollment

More Info...>>


Course Info

  • Course Number / Code:
  • 6.867 (Fall 2006) 
  • Course Title:
  • Machine Learning 
  • Course Level:
  • Graduate 
  • Offered by :
  • Massachusetts Institute of Technology (MIT)
    Massachusetts, United States  
  • Department:
  • Electrical Engineering and Computer Science 
  • Course Instructor(s):
  • Prof. Tommi Jaakkola

    Teaching Assistants:
    Ali Mohammad
    Rohit Singh 
  • Course Introduction:
  •  


  • 6.867 Machine Learning



    Fall 2006




    Course Highlights




    6.867 Machine Learning



    Fall 2006


    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.)


    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.

    Recommended Citation


    For any use or distribution of these materials, please cite as follows:

    Tommi Jaakkola, course materials for 6.867 Machine Learning, Fall 2006. MIT OpenCourseWare (http://ocw.mit.edu/), Massachusetts Institute of Technology. Downloaded on [DD Month YYYY].



    Technical Requirements


    Special software is required to use some of the files in this course: .m, .dat, and .zip.

     

ACKNOWLEDGEMENT:
This course content is a redistribution of MIT Open Courses. Access to the course materials is free to all users.






© 2009-2018 HigherEdSpace.com, All Rights Reserved.
Higher Ed Space ® is a registered trademark of AmeriCareers LLC.