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Deep Learning in Natural Language Processing Deng Lui Artificial Intelligence
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Specificaties
- Objectstaat
- Book Title
- Deep Learning in Natural Language Processing
- ISBN
- 9789811052088
Over dit product
Product Identifiers
Publisher
Springer
ISBN-10
9811052085
ISBN-13
9789811052088
eBay Product ID (ePID)
237499445
Product Key Features
Number of Pages
Xvii, 329 Pages
Language
English
Publication Name
Deep Learning in Natural Language Processing
Subject
Intelligence (Ai) & Semantics, Computer Science, Natural Language Processing, Speech & Audio Processing
Publication Year
2018
Type
Textbook
Subject Area
Computers
Format
Hardcover
Dimensions
Item Weight
24.3 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
006.35
Table Of Content
Chapter 1: A Joint Introduction to Natural Language Processing and to Deep Learning.- Chapter 2: Deep Learning in Conversational Language Understanding.- Chapter 3: Deep Learning in Spoken and Text-Based Dialogue Systems.- Chapter 4: Deep Learning in Lexical Analysis and Parsing.- Chapter 5: Deep Learning in Knowledge Graph.- Chapter 6: Deep Learning in Machine Translation.- Chapter 7: Deep Learning in Question Answering.- Chapter 8: Deep Learning in Sentiment Analysis.- Chapter 9: Deep Learning in Social Computing.- Chapter 10: Deep Learning in Natural Language Generation from Images.- 11. Epilogue: Frontiers of NLP in the Deep Learning Era.
Synopsis
Deep learning has revolutionized a number of applications in artificial intelligence, including speech, vision, natural language, game playing, healthcare, and robotics. In particular, the recent striking success of deep learning in a wide variety of Natural Language Processing (NLP) application areas has been taken as a landmark of deep learning in one of the most important tasks in Artificial Intelligence. The book presents the state-of-the-art of deep learning research, and its applications in major NLP tasks including speech recognition, lexical analysis, parsing, knowledge graph, machine translation, information retrieval, question answering, sentiment analysis, social computing, spoken language understanding, and dialogue systems. The self-contained, comprehensive chapters have been written by leading researchers in the field. It appeals to undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers and anyone interested in deep learning and natural language processing., Provides an up-to-date and comprehensive survey of deep learning research and its applications in natural language processing Covers all key tasks and techniques of natural language processing Includes contributions written by leading researchers in the respective fields, 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.
LC Classification Number
Q334-342
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