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
    29936D906Lecture9:00-10:30amMTuW77 of 120Michael ShindlerOHE122PDF (227954 KB)feesession dates
    29937R906Discussion12:30-1:30pmTuesday77 of 120OHE136session dates
    29987R906QuizTBATBA77 of 120OFFICEsession dates
    29938D911Lecture9:00-10:30amMTuW18 of 20Michael ShindlerDEN@ViterbiPDF (227954 KB)feesession dates
    29939R911Discussion12:30-1:30pmTuesday18 of 20DEN@Viterbisession dates
    29988R911QuizTBATBA18 of 20DEN@Viterbisession dates
    Information accurate as of February 15, 2019 2:46 pm.