Natural Language Processing with Spark Nlp: Learning to Understand Text at Scale

Name: Natural Language Processing with Spark Nlp: Learning to Understand Text at Scale
Brand: O'Reilly Media
SKU: 9781492047766
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ISBN13: 9781492047766
Binding: Paperback
Subject: N/A
Publisher: O'Reilly Media
Publisher Imprint: O'Reilly Media
Publication Date: August 4, 2020
Pages: N/A
Original Price: USD 79.99
Language: English
Edition: N/A
Item Weight: 581 grams
BISAC Subject(s): Artificial Intelligence / Natural Language Processing

About The Book

If you want to build an enterprise-quality application that uses natural language text but arenÃ¢ t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library.

Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. YouÃ¢ ll also explore special concerns for developing text-based applications, such as performance.

In four sections, youÃ¢ ll learn NLP basics and building blocks before diving into application and system building:

Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning
Building blocks: Learn techniques for building NLP applicationsÃ¢ including tokenization, sentence segmentation, and named-entity recognitionÃ¢ and discover how and why they work
Applications: Explore the design, development, and experimentation process for building your own NLP applications
Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support

About The Author

Thomas, Alex: - Alex Thomas is a data scientist at Indeed. He has used natural language processing (NLP) and machine learning with clinical data, identity data, and now employer and jobseeker data. He has worked with Apache Spark since version 0.9, and has worked with NLP libraries and frameworks including UIMA and OpenNLP.

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