Industrial and Systems Engineering 568:

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.
  • Crosslist: This course is offered by the CSCI department but may qualify for major credit in ISE. To register, enroll in CSCI 567.
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.