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Undergraduate and Graduate Programs 2021-2022

EEE 486 Statistical Foundations of Natural Language Processing

Introduction to Natural Language Processing (NLP). Review of linguistic preliminaries. Review of mathematical foundations. Linguistic preprocessing: tokenization, lemmatization, Part-of-Speech (PoS) tagging, stop words. Hypothesis testing. Statistical estimators in the context of NLP. Evaluation measures. Collocations, n-gram models, word-sense disambiguation. Lexical semantics. Vector space models. Word embeddings. Hidden Markov Models (HMMs) and PoS tagging. Selective applications of NLP and relation of NLP to computational social science. Credit units: 3 ECTS Credit units: 5, Prerequisite: (MATH 241 or MATH 225 or MATH 220) and (MATH 255 or MATH 230 or MATH 250).

Spring Semester (Aykut KoƧ)

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