Real-World Natural Language Processing: Practical applications with deep learning

Hagiwara, Masato

ISBN 10: 1617296422 / ISBN 13: 9781617296420

Verlag: Manning, 2021

Beschreibung

This copy may contain significant wear, including bending, heavy writing, tears, and or water damage. This book is a functional copy, not necessarily a beautiful copy. Copy may have loose pages. May not include access codes or CDs. May be an Ex library book with stickers and stamps. Dustjacket may be missing.

Bestandsnummer des Verkäufers GBV.1617296422.A

Bibliografische Details

• Titel: Real-World Natural Language Processing: Practical applications with deep learning
• Verlag: Manning
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 1617296422
• ISBN-13: 9781617296420
• Einband: Softcover
• Zustand: acceptable

Über diesen Titel

Inhaltsangabe

Voice assistants, automated customer service agents, and other cutting-edge human-to-computer interactions rely on accurately interpreting language as it is written and spoken.   Real-world Natural Language Processing  teaches you how to create practical NLP applications without getting bogged down in complex language theory and the mathematics of deep learning. In this engaging book, you’ll explore the core tools and techniques required to build a huge range of powerful NLP apps. about the technologyNatural language processing is the part of AI dedicated to understanding and generating human text and speech. NLP covers a wide range of algorithms and tasks, from classic functions such as spell checkers, machine translation, and search engines to emerging innovations like chatbots, voice assistants, and automatic text summarization. Wherever there is text, NLP can be useful for extracting meaning and bridging the gap between humans and machines. about the book Real-world Natural Language Processing  teaches you how to create practical NLP applications using Python and open source NLP libraries such as AllenNLP and Fairseq. In this practical guide, you’ll begin by creating a complete sentiment analyzer, then dive deep into each component to unlock the building blocks you’ll use in all different kinds of NLP programs. By the time you’re done, you’ll have the skills to create named entity taggers, machine translation systems, spelling correctors, and language generation systems.   what's inside

• Design, develop, and deploy basic NLP applications
• NLP libraries such as AllenNLP and Fairseq
• Advanced NLP concepts such as attention and transfer learning

about the readerAimed at intermediate Python programmers. No mathematical or machine learning knowledge required. about the author Masato Hagiwara  received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.

Über die Autorin bzw. den Autor

Masato Hagiwara received his computer science PhD from Nagoya University in 2009, focusing on Natural Language Processing and machine learning. He has interned at Google and Microsoft Research, and worked at Baidu Japan, Duolingo, and Rakuten Institute of Technology. He now runs his own consultancy business advising clients, including startups and research institutions.