6 867 Machine Learning Problem Sets And Quizzes

Collaboration is encouraged while solving problems, however you must write your own solution to every problem. Please list your collaborators on every homework that you turn in. Copying will not be tolerated. We will be holding a mid-term, on October 17th, and a final exam on December 5th. Both exams will be in class. Each student will be responsible for a project of their own selection (subject to approval).

The projects are due on Wednesday, December 11th. Robotic mannequin, "Manny", constructed at Pacific Northwest Laboratory. (Image is taken from Department of Energy's Digital Archive.) 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... 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.

See related courses in the following collections: Ali Mohammad and Rohit Singh prepared the problem sets and solutions. p1.zip (ZIP) (The ZIP file contains: 3 .m files and 4 .dat files.) p3.zip (ZIP - 8.5 MB) (The ZIP file contains: 3 .svm files.) Prob1 data (ZIP) (The ZIP file contains: 12 .m files, 1 .de file.) Prob2 data (ZIP) (The ZIP file contains: 10 .m files and 2 .dat files.)

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