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Apr 18, 2024
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DS 7337 - Natural Language Processing
Credits: 3
Introduces natural language processing (NLP) as applied to data mining, text mining, and machine learning tasks with unstructured Big Data. Students receive a broad survey of the major tasks in natural language understanding with some coverage of natural language generation. Topics include document clustering and classification, automated tagging and highlighting, semantic search, and text normalization to support machine learning applications. Focuses on best practices for choosing the right tool and method for an application, illustrated with real-world case studies. Students gain experience building solutions from real-world data sets, utilizing WordNet and the data of some leading websites. Learn text classification, clustering, tagging, and synopsizing; taxonomy alignment; corpus analytics; and semantic query analysis. Apply WordNet, Python, R, SVM, and LSA. Prerequisite: DS 7331 .
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