CSE 4392 Special Topics (Natural Language Processing)
Course Summary
Natural language processing (NLP) is the ability of a computer program to understand and further generate (mostly) human language as it is spoken and written -- referred to as natural language. It is a key component of artificial intelligence (AI), and is considered a grand challenge in AI. NLP has existed for more than 50 years and has roots in the field of linguistics. This course introduces the both classical and contempory concepts in NLP especially from a statistical and machine learning approach. It aims to provide the students with a basic understanding and appreciation of key NLP theories such as lexicons, grammar, parsing and language modeling, as well as emerging NLP applications including text classification, information retrieval, machine translation, text summarization, question answering and dialogue systems. Students will practice the knowledge acquired in this course through a team project which aims at solving one particular NLP problem of their choice.
Latest News and Announcements
- Nov 16, 2023: The new course website starts! The syllabus of the course is available on Canvas and here.!
- Jan 22, 2024: Assignment 1 released. Please choose your project team mate
ASAP!
- Jan 29, 2024: Assignment 2 released.
- Feb 5, 2024: Assignment 3 released.
- Feb 12, 2024: [Updated] We will host two sessions of research proposal presentation
this Wednesday and next Monday. Please refer to the group ids on the last page of the tutorial 4 slides to see the order of presentation. Each presentation will be 10 min long, covering the problem you are solving, the proposed solution, and the planned evaluations that you will do on your implemented systems/models. Please send your Powerpoint slides to Sinong by email in the morning on the day of your presentation, so the slides can run from our laptop to ensure smooth transition from group to group.
- Feb 12, 2024: Assignment 4 released.
- Feb 13, 2024: The announcement from yesterday is updated.
- Feb 14, 2024: We have updated the deadline for Assignment 4. Please check the new assignment files.
- Feb 17, 2024: Special Annoucement:Due to SCRF, our class on Monday, Feb 19 will be canceled. Our scheduled presentations will be moved to the following class on Wednesday. I encourage all of you to register and attend SCRF as a student participant. Enjoy the full day events of research presentations, competitions and fun there!
- Feb 29, 2024: Assignment 5 is released.
- Mar 7, 2024: Assignment 6 released.
- Mar 21, 2024: Assignment 7 released. There's a small update on the assignment sheet. Please re-download.
- Mar 27, 2024: Assignment 8 released.
- Apr 2, 2024: Important: The deadline of the research project is set on Monday Apr 29. During the class on that day,
each group will be asked to give a 10-min presentation about your own research project, including introduction, problem definition, existing approach, your approach, evaluation, and a conclusion. After the
presentation, please submit your project report + code + dataset before Midnight, May 1, 2024.
- Apr 4, 2024: Assignment 9 released.
- Announcement: Online assessment is very important to this course. We encourage all of you to provide online assessment of the course before the due data. We will reward you with 5 bonus points in the final score if more than 90% of the class complete the online assessment. Thank you!
- Apr 17, 2024: Assignment 10 is released.
Administrative Information
Lectures: Mon/Wed 2:30-3:50 PM, ERB-129.
Instructor: Kenny Zhu
- ERB-535 Phone: 3420-4592 Email: kenny[dot]zhu@uta[dot]edu
Office hours: Wed 4-5PM
Teaching Assistant:
Sinong (Theron) Wang
Email: sinong.wang[at]uta[dot]edu
Office hours: Mon 4-6PM @ ERB-316
Reference Textbooks:
- Speech and Language Processing (3rd ed) by Dan Jurafsky and James Martin, The Prentice Hall.
- Foundations of Statistical Natural Language Processing by Chritopher Manning and Hinrich Schutze, The MIT Press.
- Introduction to Information Retrieval by Christopher D. Manning, Prabhakar Raghavan, Hinrich Schütze, The Cambridge University Press.
Assessment:
- In-class quizzes: 10%
- Tutorial participation: 5% bonus
- Assignments: 30%
- Project: 30%
- Final Exam: 30%
Schedule
Copyright (c) Kenny Q. Zhu, 2023-2024.