Manning, C. and Schütze, H. Foundations of Statistical Natural Language Processing
. MIT Press. We will also be using readings from Dan Jurafsky and James Martin, Speech and Language Processing
Other Books and Resources
Mark Lutz and David Ascher, Learning Python
Chris Fehily, Python Visual QuickStart Guide
, Peachpit Press.
will be determined on the basis of performance on five assignments
(50%), a final project and presentation (40%), and class participation
(10%). The Schedule of Lectures, Readings, and Assignments
contains links to assignments, lecture slides, and specifies due dates,
etc. Information may also be disseminated via the class mailing list.
- Basic familiarity with logic, basic mathematics (logs, exponents, etc), basic probability
- Ability to use a computer, word processor. Readiness to learn a basic programming language, with hand-holding
Students can use their own computers, in which case you should install
the Natural Language ToolKit (NLTK) and required software (mainly,
Python) on your machine. Students can also use the computers in the
Asprey Lab in the Computer Science Department, which have all of the
required software already installed.