Show simple item record

dc.contributor.authorRosenfeld, Avi
dc.identifier.citationRosenfeld, Avi. (2021, Spring), Syllabus, COM 3930: Text Analysis and Natural Language Processing, Yeshiva College, Yeshiva University.en_US
dc.descriptionCourse syllabus / YU onlyen_US
dc.description.abstractDescription Vast amounts of information is created in the form of unstructured data – web pages, social media posts, emails, presentations, analysts’ reports, news content, etc. The ability to extract useful information from such data sources is a critical tool in the toolbox of a data scientist. This course examines computational methods for analyzing human language textual data in order to detect meaning and extract information. Applications of these methods include sentiment analysis, information retrieval, and trend prediction. Course Outcomes  Students will be able to articulate the fundamentals of natural language processing  Students will be able to competently use several major software packages for NLP  Students will be able to apply machine learning for text analysis  Students will be able to implement Information Retrieval Algorithms  Students will be able to implement and use Word Embedding algorithms such as Word2Vec Major Topics Covered in Course  What is natural language processing and the challenge of doing it computationally  Major tasks that NLP undertakes  Uses and limitations of n-gram analysis  Using NLP and syntactical analysis for text mining  Understanding and implementing search engines  Using and implementing modern word embedding techniques such as Word2Vecen_US
dc.relation.ispartofseriesYeshiva College Syllabi;COM 3930
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.subjectNatural Language Processing (NLP)en_US
dc.subjectcomputer programmingen_US
dc.subjectcourse syllabusen_US
dc.titleCOM 3930: Text Analysis and Natural Language Processingen_US
dc.typeLearning Objecten_US
dc.typeOpen Educational Resourcesen_US

Files in this item


This item appears in the following Collection(s)

Show simple item record

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