This class is an introduction to basic principles of machine learning. We will focus on so-called
Prerequisites: STAT UN2103. Some homework problems will involve programming. Familiarity with R is assumed.
Class specs
Time: Tue/Thu 2:40pm-3:55pm
Room: 627 Mudd
Teaching Assistant: Phyllis Wan (pw2348)
TA office hours: Tue 4-6pm, Wed 3:30-4:30pm
Instructor office hours: Tue 9-10am
Midterm exam: 8 March.
The final exam will be scheduled by the school.
Grading: 40% homework + 30% midterm exam + 30% final exam
Homework
Material
Here are the current course slides:
- Slides (16 January)
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- Slides (25 January)
- Slides (30 January)
- Slides (1 February)
- Slides (6 February)
- Slides (8 February)
- Slides (13 February)
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- Slides (20 February)
- Slides (22 February)
- Slides (27 February)
- (No slides for 20 March. Material will not be examined.)
- Slides (22 March)
- Slides (27 March)
- Slides (29 March)
- Slides (3/5 April)
- Slides (10 April)
- Slides (12 April)
- Slides (17 April)
- 19 April: Review for final exam
- Slides (24 April)
- Slides (26 April)