9789811338489-9811338485-Deep Learning in Natural Language Processing

Deep Learning in Natural Language Processing

ISBN-13: 9789811338489
ISBN-10: 9811338485
Edition: Softcover reprint of the original 1st ed. 2018
Author: Li Deng, Yang Liu
Publication date: 2018
Publisher: Springer
Format: Paperback 346 pages
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Book details

ISBN-13: 9789811338489
ISBN-10: 9811338485
Edition: Softcover reprint of the original 1st ed. 2018
Author: Li Deng, Yang Liu
Publication date: 2018
Publisher: Springer
Format: Paperback 346 pages

Summary

Deep Learning in Natural Language Processing (ISBN-13: 9789811338489 and ISBN-10: 9811338485), written by authors Li Deng, Yang Liu, was published by Springer in 2018. With an overall rating of 4.2 stars, it's a notable title among other books. You can easily purchase or rent Deep Learning in Natural Language Processing (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. 

This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided.

The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing. 

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