Natural Language Processing

UVA CS 6501-011 (Fall 2024)

Table of Contents

1. Course Information

1.1 Additional Information

Class sessions for this course will be recorded. Recordings will be available only to the instructor and students enrolled in the class. Recordings will be deleted when no longer necessary. Recordings may not be reproduced, shared with those not enrolled in the class, or uploaded to other online environments.

2. Course Description

Natural language processing (NLP) seeks to provide computers with the ability to process and understand human language intelligently. Examples of NLP techniques include (i) automatically translating from one natural language to another, (ii) analyzing documents to answer related questions or make related predictions, and (iii) generating texts to help story writing or build conversational agents. This course, consisting of one fundamental part and one advanced part, will give an overview of modern NLP techniques.

2.1 Topics

This course will mainly focus on applying machine learning (particularly, deep learning) techniques to natural language processing. NLP topics covered by this course

  1. Text classification and its applications
  2. Word embeddings
  3. Language modeling
  4. Sequence-to-sequence models and machine translation
  5. Large pre-trained models and text generation

Other advanced topics, such as explainable NLP and NLP in social science.

For detail information, please refer to the course schedule.

2.2 Prerequisites

2.3 Textbooks

Supplemental materials

3. Assignments and Final Project

3.1 Collaboration policy

For homework assignments

For the final project, replace the word “student(s)” with “group(s)”.

3.2 Computing Resources

A complementary computing resource is provided by the UVA Rivanna system, including both CPU and GPU hours. Stay tuned for more details.

3.3 Resources for the Final Project

The general theme for the final project is NLP for Social Good, which covers a wide range of problems that concern us, for example, social fairness, medical applications, and educational applications.

To get some inspirations for the final project, you can start from the following reading list.

4. Additional Information

Last updated on 04/08/2024