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
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.