SPA-621 Natural Language Processing (1)

This course covers fundamental methods for analyzing textual datasets, focusing on applying classical natural language processing (NLP) methods and libraries in Python to interesting corpora. Students gain familiarity with NLP concepts to facilitate processing of text for textual analysis. Students also learn NLP tasks such as text classification, information extraction, and topic modeling including methods based on deep learning and methods such as singular value decomposition, non-negative matrix factorization, latent Dirichlet allocation, and independent component analysis. Crosslist: SPA-421. Usually Offered: summer.