This is a class on machine learning methods that are useful to NLP problems.

### Schedule

- Lectures: T Th 1:30-2:50pm FriendCenter 008
- P1: M 10:00-10:50am Friend Center 108
- P2: W 1:30-2:20pm FriendCenter 110
- Office hours:
- Sida: W 12:30-1:30pm, 3:30-4:30pm CS 413
- Mark: Th 11:30am-1:30pm CS basement
- Misha: M 1:00-3:00pm CS 331

### Staff

- Instructor: Sida Wang
- TA: Misha Khodak
- TA: Mark Martinez

### Grading

- Assignments: 18% x 3
- Project: 30%
- Midterm: 16%
- Up to 2% bonus for participation on Piazza and in class

You can work in groups of 1-2 for assignments, and 1-3 for the project. There are 5 late days in total, with a maximum 2 late days per assignment. Assignments are due on 11:55pm, the due date can be found in the class schedule. Assignment code and report should be uploaded to Dropbox.

### Background

- Multivariate calculus, linear algebra, programming (python in particular)
- Probability, statistics, and machine learning helpful