Examine basic machine learning methods, with an emphasis on building applications that intelligently analyze text. Explore supervised learning (e.g., logistic regression, neural networks), unsupervised learning (e.g., clustering), and natural language processing. Three lecture hours a week for one semester. Only one of the following may be counted: Linguistics 371, 373 (Topic: Machine Learning Text Analysis), 373N. Prerequisite: Upper-division standing and one of the following: Linguistics 350 (Topic 12), Computer Science 303E, 312, or basic programming experience in Python or similar languages.