Natural Language Processing with Spark NLP (e-bog) af Thomas, Alex
Thomas, Alex (forfatter)

Natural Language Processing with Spark NLP e-bog

359,43 DKK (inkl. moms 449,29 DKK)
If you want to build an enterprise-quality application that uses natural language text but arent 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 ...
E-bog 359,43 DKK
Forfattere Thomas, Alex (forfatter)
Udgivet 25 juni 2020
Længde 366 sider
Genrer UYQL
Sprog English
Format epub
Beskyttelse LCP
ISBN 9781492047711
If you want to build an enterprise-quality application that uses natural language text but arent 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. Youll also explore special concerns for developing text-based applications, such as performance.In four sections, youll 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 learningBuilding blocks: Learn techniques for building NLP applicationsincluding tokenization, sentence segmentation, and named-entity recognitionand discover how and why they workApplications: Explore the design, development, and experimentation process for building your own NLP applicationsBuilding NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support