COMP 4930H Topics: Natural Language Processing

dc.contributor.author	Waxman, Joshua
dc.date.accessioned	2021-11-02T17:22:57Z
dc.date.available	2021-11-02T17:22:57Z
dc.date.issued	2021-01
dc.identifier.citation	Waxman, Joshua. (2021, Spring), Syllabus, COMP 4930H Topics: Natural Language Processing, Stern College for Women, Yeshiva University.	en_US
dc.identifier.uri	https://hdl.handle.net/20.500.12202/7649
dc.description	SCW syllabus / YU only	en_US
dc.description.abstract	Overview: We will explore algorithms for understanding and producing human language. We will consider NLP applications of tokenization, word and sentence segmentation, part-of-speech tagging, morphological analysis, syntax parsing, and more. We will explore the overlap between NLP, information retrieval, machine learning and deep learning. Practically, we will implement many of these algorithms or utilize popular NLP frameworks to apply these algorithms. Prerequisites: Data Structures and Calculus	en_US
dc.language.iso	en_US	en_US
dc.relation.ispartofseries	SCW Syllabi;COMP 4930H
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 United States	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.subject	human language production	en_US
dc.subject	tokenization	en_US
dc.subject	morphological analysis	en_US
dc.subject	syntax parsing	en_US
dc.subject	algorithms	en_US
dc.subject	NLP frameworks	en_US
dc.title	COMP 4930H Topics: Natural Language Processing	en_US
dc.type	Learning Object	en_US

Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States