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
    29984R048QuizTBATBA412 of 600OFFICEsession dates
    30352D048Lecture5:00-7:20pmTuesday
    200 of 200
    		Victor AdamchikSGM123feesession dates
    30392R048Discussion7:30-8:20pmTuesday202 of 300SGM123session dates
    29995D048Lecture5:00-7:20pmThursday
    212 of 200
    		Victor AdamchikSGM123feesession dates
    30151R048Discussion7:30-8:20pmThursday210 of 300SGM123session dates
    30259D034Lecture5:00-7:20pmThursday14 of 20Victor AdamchikDEN@Viterbifeesession dates
    30272R034Discussion7:30-8:20pmThursday14 of 20DEN@Viterbisession dates
    29985R034QuizTBATBA14 of 30DEN@Viterbisession dates
    Information accurate as of October 10, 2019 1:02 pm.