SIMS 290-2: Applied Natural Language Processing
   Fall 2004, Prof. Marti Hearst

Course Information

Administrivia

Instructor:

Marti Hearst (hearst@sims)
212 South Hall, 510-642-8016
Office Hours: Wed 2-3pm, Thurs 2-3pm, 212 South Hall

TAs:

Preslav Nakov
Office Hours: TBD
Barbara Rosario
Office Hours: TBD

Class Meetings

Class meets on Monday and Wednesday from 10:30-12:00 in 202 South Hall. The format of the class will be primarily lecturing and in-class experimentation with NLP software.

Prerequisites

IS255, a CS background, or equivalent. This class will involve using various software tools and writing code to glue them together. We will be using the Python programming language.

Grading

There will be three mini-projects (70% of grade) as well as 3-4 other short homework exercises (30% of grade). The final mini-project will include a writeup and class presentation, and so grades on it will be based on a combination of presentations, write-ups, and the mini-project itself.

Most work will be done in groups of size two or three, but individual homework should be done independently. It is fine to discuss the general techniques and methods required, but you must do your own work in solving the problems and writing up the solutions.

Late Policy

Late assignments will be penalized with a reduction in grade unless otherwise approved by the instructor.

Readings and Books

Unfortunately, there really is not appropriate textbook for this course. Instead we will be reading online readings and handouts.

Students will need to learn a bit of Python programming for this course, and so an introductory Python book is recommended.

See resources for suggested books.