Computer Science 4750:
Introduction to Natural Language Processing
Lecture Outline (Tentative)
- Background: Linguistics and Natural Language Processing (2 weeks)
- Mechanisms for Natural Language Processing (1 1/2 weeks)
- Implementing NLP Mechanisms (Finite-state Automata and Transducers, Context-free Grammars, Hidden Markov Models, Neural Networks)
- Applications (e.g., Information Extraction, Spelling Correction, Machine Translation) (2 weeks)
- Student presentations (2 weeks)
The lectures and displays (and all material) delivered or provided in this course by the instructor,
including any visual or audio recording thereof, are subject to copyright
owned by the instructor.. It is prohibited to record or copy by any means, in any format,
openly or surreptitiously, in whole or in part, in the absence of express written permission from
the instructor any of the lectures or materials provided or published in any form during or from
|Class Exams (3)
||Monday, October 4
Friday, November 5
Friday, November 26
||Monday, November 29 --
Friday, December 3
|Course Project Proposal
||Thursday, November 4
||Friday, December 3
- There will be no supplementary assignments. Extensions for missed assignments (with appropriate
documentation) will be given at the instructor's discretion. Where such
extensions are not given, either (1) late assignments will be docked 25% or (2) marks for missed assignments
documentation) will be averaged over the remaining assignments at the instructor's discretion.
- There will be no supplementary exams. Marks for missed in-class exams (with appropriate
documentation) will be averaged over the remaining exams at the instructor's discretion.
Assignment Deadlines (Tentative)
|Assignment #1||Sep 8||Sep 24 |
|Assignment #2||Sep 24||Oct 29 |
|Assignment #3||Oct 22||Nov 19 |
- Bird, S., Klein, E., and Loper, E. (2009) Natural Language Processing with
Python. O'Reilly Media.
- Eisenstein, J. (2019) Introduction to Natural Language
Processing. The MIT Press.
- Indurkhya, N. and Damerau, F.J. (eds.) (2010) Handbook of Natural
Language Processing (2nd Edition). Chapman and Hall / CRC.
- Jurafsky, D. and Martin, J.H. (2008) Speech and Natural Language
Processing (2nd Edition). Prentice-Hall.
- Kedia, A, and Rasu, M. (2020) Hands-On Python Natural Language
Processing. Packt Publishing; Birmingham, UK.
- Mitkov, R. (ed.) (2005) The Oxford Handbook of Computational
Linguistics. Oxford University Press.
- Rao, D. and McMahan, B. (2019) Natural Language Processing with
PyTorch: Build Intelligent Language Applications Using Deep
Learning. O'Reilly; Boston.
- Roche, E. and Schabes, Y. (eds.) (1997) Finite-state Natural Language
Processing. The MIT Press.
- Vajjala, S., Majumder, B., Gupta, A., and Surana, H. (2019)
Practical Natural Language Processing: A Comprehensive Guide to
Building Real-world NLP Systems. O'Reilly; Boston, MA.
- Memorial University of Newfoundland is committed to supporting inclusive education
based on the principles of equity, accessibility, and collaboration. Accommodations
are provided within the scope of the University Policies for the Accommodations of
Students with Disabilities (
Students who may need an academic accommodation are asked to initiate the request with
the Glenn Roy Blundon Centre at the earliest opportunity
- Students are expected to adhere to those principles which constitute proper
academic conduct. A student has the responsibility to know which actions, as described
under Academic Offences in the University Regulations, could be construed as dishonest and
improper. Students found guilty of an academic offence may be subject to a number of penalties
commensurate with the offence including reprimand, reduction of grade, probation, suspension or
expulsion from the University. For more information regarding this policy, students should
refer to the University Regulations for Academic Misconduct
(Section 6.12) in the
Created: July 19, 2021
Last Modified: October 18, 2021