Computer Science 567:

Machine Learning (4.0 units)

Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.
    SectionSessionTypeTimeDaysRegisteredInstructorLocationSyllabusInfo
    30079D048Lecture10:00-11:50amWed, Fri82 of 90Yan LiuOHE132feesession dates
    30081R048DiscussionTBATBA82 of 90OFFICEsession dates
    30265R048QuizTBATBA82 of 90OFFICEsession dates
    30213D034Lecture10:00-11:50amWed, Fri15 of 30Yan LiuDEN@Viterbifeesession dates
    30264R034DiscussionTBATBA15 of 30DEN@Viterbisession dates
    30266R034QuizTBATBA15 of 30DEN@Viterbisession dates
    Information accurate as of July 10, 2020 1:51 pm.
    All Summer 2020 courses will be taught remotely. Faculty will contact students to provide information to login to classes.