Natural Language Annotation for Machine Learning : A Guide to Corpus-Building for Applications

Amber Stubbs

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Language: English

Published by O'reilly Media Dez 2012, 2012

1449306667 / 9781449306663

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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.

Seller Inventory # 9781449306663

Title
Natural Language Annotation for Machine Learning : A Guide to Corpus-Building for Applications
Author
Amber Stubbs
Publisher
O'reilly Media Dez 2012
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
1449306667
ISBN 13
9781449306663
Item weight
624 grams
Dimensions
231x179x25 mm

AHA-BUCH GmbH

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