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Natural Language Annotation Machine by Pustejovsky James (19 results)
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Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications
Published by O'Reilly Media (edition 1), 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Language: English
Paperback. Condition: Good. 1. It's a preowned item in good condition and includes all the pages. It may have some general signs of wear and tear, such as markings, highlighting, slight damage to the cover, minimal wear to the binding, etc., but they will not affect the overall reading experience.
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Condition: very_good. Fast & Free Shipping â" Very good condition with a clean, sturdy cover and crisp pages. Gently used with only minor shelf wear. May include a few subtle marks, but overall a well-maintained copy ready to enjoy.Supplemental items like CDs or access codes may not be included.
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Paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Condition: good. Signs of wear and consistent use.
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Paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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paperback. Condition: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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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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Condition: As New. Unread book in perfect condition.
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Condition: very good. Gently used. May include previous owner's signature or bookplate on the front endpaper, sticker on back and/or remainder mark on text block.
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Natural Language Annotation for Machine Learning: A Guide to Corpus-Building for Applications (Paperback or Softback)
Published by O'Reilly Media 11/4/2012, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Language: English
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
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
Published by Oreilly & Associates Inc, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Language: English
Paperback. Condition: Brand New. 1st edition. 326 pages. 9.25x7.00x0.75 inches. In Stock.
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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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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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Natural Language Annotation for Machine Learning : A Guide to Corpus-Building for Applications
Published by O'reilly Media Dez 2012, 2012
ISBN 10: 1449306667 ISBN 13: 9781449306663
Language: English
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.
