Read Bayesian Analysis in Natural Language Processing

Bayesian Analysis in Natural Language Processing

Shay Cohen

4.9/5 (18269 ratings)

Description:Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples.We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis. Source: http://www.morganclaypoolpublishers.c...Table of Contents:PrefaceAcknowledgmentsPreliminariesIntroductionPriorsBayesian EstimationSampling MethodsVariational InferenceNonparametric PriorsBayesian Grammar ModelsClosing RemarksBibliographyAuthor's BiographyIndexWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Bayesian Analysis in Natural Language Processing. To get started finding Bayesian Analysis in Natural Language Processing, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 274

Format: PDF, EPUB & Kindle Edition

Publisher: Morgan & Claypool

Release: 2016

ISBN: 1627058737

Description: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples.We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis. Source: http://www.morganclaypoolpublishers.c...Table of Contents:PrefaceAcknowledgmentsPreliminariesIntroductionPriorsBayesian EstimationSampling MethodsVariational InferenceNonparametric PriorsBayesian Grammar ModelsClosing RemarksBibliographyAuthor's BiographyIndexWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Bayesian Analysis in Natural Language Processing. To get started finding Bayesian Analysis in Natural Language Processing, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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Bayesian Analysis in Natural Language Processing

Bayesian Analysis in Natural Language Processing

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