Fall 2019 - CMPT 825 G100
Natural Language Processing (3)
Class Number: 9027
Delivery Method: In Person
Course Times + Location:
Sep 3 – Dec 2, 2019: Tue, 4:30–5:20 p.m.
Sep 3 – Dec 2, 2019: Thu, 3:30–5:20 p.m.
Exam Times + Location:
Dec 14, 2019
Sat, 3:30–6:30 p.m.
1 778 782-2015
In this course, theoretical and applied issues related to the development of natural language processing systems and specific applications are examined. Investigations into parsing issues, different computational linguistic formalisms, natural language syntax, semantics, and discourse related phenomena will be considered and an actual natural language processor will be developed.
This course is cross-listed with CMPT 413
Imagine a world where you can pick up a phone and talk in English, while at the other end of the line your words are spoken in Chinese. Imagine a computer animated representation of yourself speaking fluently what you have written in an email. Imagine automatically uncovering protein/drug interactions in petabytes of medical abstracts. Imagine feeding a computer an ancient script that no living person can read, then listening as the computer reads aloud in this dead language. Natural Language Processing is the automatic analysis of human languages such as English, Korean, and thousands of others analyzed by computer algorithms that can make these applications possible. Unlike artificially created programming languages where the structure and meaning of programs is easy to encode, human languages provide an interesting challenge, both in terms of its analysis and the learning of language from observations.
- Language models
- Edit distance
- Supervised machine learning for NLP
- Sequence labeling
- Unsupervised machine learning for NLP
- Machine translation
- Parsing and semantics
Final Project: 30%. 1 Midterm: 20%. 5 Homeworks: 45%. Participation 5%.
Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C- or better).
Graduate Studies Notes:
Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS