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9781449306663 - Natural Language Annotation for Machine Learning: a Guide to Corpus-building for Applications by Pustejovsky, Associate Professor of Computer Science James; Stubbs,... (30 results)
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Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications
Language: English
Published by O'Reilly Media (edition 1), 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Paperback. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Natural Language Annotation for Machine Learning : A Guide to Corpus-Building for Applications
Language: English
Published by O'Reilly Media, Incorporated, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Condition: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Natural Language Annotation for Machine Learning
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications
Seller: WorldofBooks, Goring-By-Sea, WS, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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Paperback. Condition: New. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You'll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations. This book is a perfect companion to O'Reilly's Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.
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Natural Language Annotation for Machine Learning
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You'll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations. This book is a perfect companion to O'Reilly's Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.
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Natural Language Annotation for Machine Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Natural Language Annotation for Machine Learning
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Natural Language Annotation for Machine Learning
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
First Edition
Condition: New. 2012. 1st Edition. Paperback. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Num Pages: 346 pages, Illustrations. BIC Classification: UYQL. Category: (XV) Technical / Manuals. Dimension: 233 x 179 x 19. Weight in Grams: 560. . . . . .
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Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications (Paperback or Softback)
Language: English
Published by O'Reilly Media 11/4/2012, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Paperback or Softback. Condition: New. Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications. Book.
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Natural Language Annotation for Machine Learning
Language: English
Published by O'Reilly Media, Inc, USA, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Condition: New. 2012. 1st Edition. Paperback. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Num Pages: 346 pages, Illustrations. BIC Classification: UYQL. Category: (XV) Technical / Manuals. Dimension: 233 x 179 x 19. Weight in Grams: 560. . . . . . Books ship from the US and Ireland.
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Natural Language Annotation for Machine Learning
Language: English
Published by Oreilly & Associates Inc, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Paperback. Condition: Brand New. 1st edition. 326 pages. 9.25x7.00x0.75 inches. In Stock.
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paperback. Condition: Good.
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Paperback. Condition: New. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You'll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations. This book is a perfect companion to O'Reilly's Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.
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Kartoniert / Broschiert. Condition: New. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a gold.
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Paperback. Condition: New. Create your own natural language training corpus for machine learning. This example-driven book walks you through the annotation cycle, from selecting an annotation task and creating the annotation specification to designing the guidelines, creating a "gold standard" corpus, and then beginning the actual data creation with the annotation process. Systems exist for analyzing existing corpora, but making a new corpus can be extremely complex. To help you build a foundation for your own machine learning goals, this easy-to-use guide includes case studies that demonstrate four different annotation tasks in detail. You'll also learn how to use a lightweight software package for annotating texts and adjudicating the annotations. This book is a perfect companion to O'Reilly's Natural Language Processing with Python, which describes how to use existing corpora with the Natural Language Toolkit.
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Natural Language Annotation for Machine Learning : A Guide to Corpus-Building for Applications
Language: English
Published by O'reilly Media Dez 2012, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Taschenbuch. Condition: Neu. Neuware - Create your own natural language training corpus for machine learning. Whether you're working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle - the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don't need any programming or linguistics experience to get started.Using detailed examples at every step, you'll learn how the MATTER Annotation Development Process helps you Model, Annotate, Train, Test, Evaluate, and Revise your training corpus. You also get a complete walkthrough of a real-world annotation project. Define a clear annotation goal before collecting your dataset (corpus) Learn tools for analyzing the linguistic content of your corpus Build a model and specification for your annotation project Examine the different annotation formats, from basic XML to the Linguistic Annotation Framework Create a gold standard corpus that can be used to train and test ML algorithms Select the ML algorithms that will process your annotated data Evaluate the test results and revise your annotation task Learn how to use lightweight software for annotating texts and adjudicating the annotationsThis book is a perfect companion to O'Reilly's Natural Language Processing with Python.
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Natural Language Annotation for Machine Learning
Language: English
Published by Oreilly & Associates Inc, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Paperback. Condition: Brand New. 1st edition. 326 pages. 9.25x7.00x0.75 inches. In Stock. This item is printed on demand.
