Speech and Language Processing
by Dan Jurafsky, James H. Martin
Publisher: Stanford University 2017
Number of pages: 499
This text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. The authors cover areas that traditionally are taught in different courses, to describe a unified vision of speech and language processing. Emphasis is on practical applications and scientific evaluation.
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by Daniël de Kok, Harm Brouwer
We will go into many of the techniques that so-called computational linguists use to analyze the structure of human language, and transform it into a form that computers work with. We chose Haskell as the main programming language for this book.
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This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies. With it, you'll learn how to write Python programs that work with large collections of unstructured text.
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What kind of computational device could use a system like a human language? This text explores the computational properties of devices that could compute morphological and syntactic analyses, and recognize semantic relations among sentences.
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