Create your own natural language trainingcorpus for machine learning. Whether you’re working with English, Chinese, orany other natural language, this hands-on book guides you through a provenannotation development cycle—the process of adding metadata to your trainingcorpus to help ML algorithms work more efficiently. You don’t need anyprogramming or linguistics experience to get started.
Using detailed examples at every step, you’ll learn how the MATTER AnnotationDevelopment Process helps you Model, Annotate, Train, Test, Evaluate, and Reviseyour training corpus. You also get a complete walkthrough of a real-worldannotation 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
This book is a perfectcompanion to O’Reilly’s Natural Language Processing with Python.
