Simon Fraser University
Engaging the World

Course Outlines

Fall 2020 - CMPT 825 G100

Natural Language Processing (Inactive) (3)

Class Number: 6681

Delivery Method: In Person

Overview

  • Course Times + Location:

    Sep 9 – Dec 8, 2020: Wed, 11:30 a.m.–12:20 p.m.
    Burnaby

    Sep 9 – Dec 8, 2020: Fri, 10:30 a.m.–12:20 p.m.
    Burnaby

  • Exam Times + Location:

    Dec 11, 2020
    Fri, 3:30–6:30 p.m.
    Burnaby

Description

CALENDAR DESCRIPTION:

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.

COURSE DETAILS:

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 instructing a robot to prepare your backpack for you. 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.

Topics

  • Language models
  • Word representations
  • Supervised machine learning for NLP
  • Neural models for NLP
  • Sequence labeling
  • Machine translation
  • Parsing and semantics
  • NLP applications

Grading

  • Grading will be based on assignments, final project and class participation. Details will be announced during the first week of classes. 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).

Materials

MATERIALS + SUPPLIES:

Reference Books

  • Speech and Language Processing (3rd ed), Dan Jurafsky and James H. Martin, 2019, https://web.stanford.edu/~jurafsky/slp3/
  • Neural Network Methods for Natural Language Processing, Yoav Goldberg, Morgan and Claypool, 2017, http://www.morganclaypool.com/doi/10.2200/S00762ED1V01Y201703HLT037
  • Natural Language Processing, Jacob Eisenstein, The MIT Press, 2018, https://github.com/jacobeisenstein/gt-nlp-class/blob/master/notes/eisenstein-nlp-notes.pdf

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.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

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

TEACHING AT SFU IN FALL 2020

Teaching at SFU in fall 2020 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.

Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112).