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
29995D048Lecture1:00-3:20pmFriday243 of 330Dani YogatamaSGM123session dates
30151R048Discussion3:30-4:20pmFriday243 of 330SGM123session dates
29984R048QuizTBATBA243 of 330OFFICEsession dates
30259D034Lecture1:00-3:20pmFriday15 of 30Dani YogatamaDEN@Viterbisession dates
30272R034Discussion3:30-4:20pmFriday15 of 30DEN@Viterbisession dates
29985R034QuizTBATBA15 of 30DEN@Viterbisession dates
Information accurate as of January 19, 2024 5:02 pm.