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LING-420 Introduction to Statistical Natural Language Processing
Fall for 2010-2011
Anton Rytting
Anyone wishing to work in natural language processing (NLP) must have some understanding of the statistical methods in common practice. This course will introduce you to the fundamentals of statistical NLP. Statistical NLP builds on ideas from many fields, including linguistics, probability theory, information theory, programming, and computer science. We will see how these fields provide us with tools to engage in part-of-speech (POS) tagging, parsing, word sense disambiguation, machine translation, and information retrieval.

The focus of the course is very data-driven, meaning that students will be working with large corpora and will be learning how to handle such large pieces of data. Applying statistical techniques to large corpora will also allow us to examine collocations and n-grams, along with techniques for categorizing text.
Credits: 3
Prerequisites: None
More information
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Georgetown University37th and O Streets, N.W., Washington D.C. 20057(202) 687.0100

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