CS 5740

Natural Language Processing

Course Description

Course information provided by the Courses of Study 2022-2023.

This course constitutes an introduction to natural language processing (NLP), the goal of which is to enable computers to use human languages as input, output, or both. NLP is at the heart of many of today's most exciting technological achievements, including machine translation, automatic conversational assistants and Internet search. Possible topics include: methods for handling underlying linguistic phenomena (e.g., syntactic analysis, word sense disambiguation and discourse analysis) and vital emerging applications (e.g., machine translation, sentiment analysis, summarization and information extraction).

When Offered Fall, Spring.

Prerequisites/Corequisites Prerequisite: CS 2110 or equivalent programming experience; Spring - CS 4780 and CS 4786, or CS 5785 or equivalent machine learning experience. Recommended prerequisite: strong familiarity with Python and ideally some form of numerical library (e.g., numpy, scipy, scikit-learn, torch, tensorflow), a strong understanding of foundational CS concepts such as memory requirements and computational complexity. Recommended prerequisite for math: students need to be comfortable with calculus and probability, primarily differentiation and basic discrete distributions.

Comments This course is programming intensive, and does not require proofs.

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