Natural Language Processing with Spark NLP Learning to Understand Text at Scale
Natural Language Processing with Spark NLP Learning to Understand Text at Scale by Alex Thomas is a practical guide published by O’Reilly Media in 2020, featuring 347 pages in English. This book is designed for software engineers and data scientists looking to develop enterprise-quality applications that utilize natural language text. It provides a comprehensive introduction to building scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library.
Readers will find a structured approach that covers the fundamentals of natural language processing, including basic linguistics and writing systems, as well as advanced topics like sentiment analysis and search engines. The book is divided into four sections, guiding readers through the basics and building blocks of NLP before moving on to application design and system development. It also addresses practical considerations for developing text-based applications, such as performance and deployment options, making it a valuable resource for those interested in data science and artificial intelligence.
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If you want to build an enterprise-quality application that uses natural language text but arenÃfÂfÃ,¢??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. YouÃfÂfÃ,¢??ll also explore special concerns for developing text-based applications, such as performance.
In four sections, youÃfÂfÃ,¢??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 applicationsÃfÂfÃ,¢??including tokenization, sentence segmentation, and named-entity recognitionÃfÂfÃ,¢??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
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