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Natural Language Annotation for Machine Learning

Natural Language Annotation for Machine Learning
By James Pusetjovosky and Amber Stubbs

Retail Price $39.99
Amazon Price: $28.50

Book Description:

    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 annotations



Book Bargains Review



This book is an introductory book to using natural language in machine learning.   It's not a textbook, but is a how-to guide that will walk you through understanding the annotation process from a data-oriented perspective, writing the code, visualizing your work in progress, and getting to a useful result.
The text gives the reader a solid introduction to Python along with some language analysis tools and is then taught how to load corpa (large collections of text) both those provided by the NLTK (Natural Language Tool Kit) team, as well as the users own corpa.   I highly recommend it, particularly for developers who want to build their machine learning toolset.  While you won't have a complete understanding of computer science when you are done with this book, you will equipped with most of the knowledge of programming that you will need to do most language processing tasks.


~Reviewed by David H.

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