EEE 486 Statistical Foundations of Natural Language Processing
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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 or MATH 224) and (MATH 255 or MATH 230 or MATH 250).
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