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This course is a graduate introduction to natural language processing - the study of human language from a computational perspective.

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1

English

English [CC]

FREE

Description

It covers syntactic, semantic and discourse processing models, emphasizing machine learning or corpus-based methods and algorithms. It also covers applications of these methods and models in syntactic parsing, information extraction, statistical machine translation, dialogue systems, and summarization. The subject qualifies as an Artificial Intelligence and Applications concentration subject.

Course content

  • Introduction and Overview Unlimited
  • Parsing and Syntax I Unlimited
  • Smoothed Estimation, and Language Modeling Unlimited
  • Parsing and Syntax II Unlimited
  • The EM Algorithm Unlimited
  • The EM Algorithm Part II Unlimited
  • Lexical Similarity Unlimited
  • Lexical Similarity (cont.) Unlimited
  • Log-Linear Models Unlimited
  • Tagging and History-based Models Unlimited
  • Grammar Induction Unlimited
  • Computational Modeling of Discourse Unlimited
  • Text Segmentation Unlimited
  • Local Coherence and Coreference Unlimited
  • Machine Translation Unlimited
  • Machine Translation (cont.) Unlimited
  • Graph-based Methods for NLP Applications Unlimited
  • Word Sense Disambiguation Unlimited
  • Global Linear Models Unlimited
  • Global Linear Models Part II Unlimited
  • Dialogue Processing Unlimited
  • Dialogue Processing (cont.) Unlimited
  • Text Summarization Unlimited

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Instructor

Massachusetts Institute of Technology
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