Natural Language Processing

Catalog description

Natural language processing (NLP), a form of artificial intelligence (AI) that gives computers the ability to read, understand and interpret human languages, is one of the most important technologies that have made significant progress recently. NLP has been applied to many areas such as spoken dialogue system, machine translation, question and answering, machine reading, document summarization, and even music generation. Traditional NLP approaches involve rules that are handcrafted by linguists. On the other hand, modern NLP approaches are data-driven, trying to learn a model to minimize a target loss function over labeled or unlabeled training text. The course will cover various NLP techniques such as text classification, sequence classification, parse trees, and sequence-to-sequence generation from statistical or deep learning perspectives. Students will be expected to derive mathematical formulas, and code and tune NLP algorithms on datasets in homework assignments. Prerequisite: CSCI-SHU 11 Introduction to Computer Programming and ( CSCI-SHU 360 Marchine Learning or MATH-SHU 235 Probability and Statistic or MATH-SHU 238 Theory of Probability) Fulfillment: CS elective; DS AI concentration. Equivalencies: CSCI-UA 480 (Topic must be: Natural Language Processing)