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)
- Slides (18 January)
- Slides (23 January)
- Slides (25 January)
- Slides (30 January)
- Slides (1 February)
- Slides (6 February)
- Slides (8 February)
- Slides (13 February)
- Slides (15 February)
- 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)