Deep Learning and Linguistic Representation

By:

Shalom Lappin

Format:

Paperback / softback

Series:

Chapman & Hall/CRC Machine Learning & Pattern Recognition

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Description

The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of these applications, deep learning models now approach or surpass human performance. While the success of this approach has transformed the engineering methods of machine learning in artificial intelligence, the significance of these achievements for the modelling of human learning and representation remains unclear. Deep Learning and Linguistic Representation looks at the application of a variety of deep learning systems to several cognitively interesting NLP tasks. It also considers the extent to which this work illuminates our understanding of the way in which humans acquire and represent linguistic knowledge. Key Features: combines an introduction to deep learning in AI and NLP with current research on Deep Neural Networks in computational linguistics. is self-contained and suitable for teaching in computer science, AI, and cognitive science courses; it does not assume extensive technical training in these areas. provides a compact guide to work on state of the art systems that are producing a revolution across a range of difficult natural language tasks.

Author Biography:

Shalom Lappin is Professor of Natural Language Processing at Queen Mary University of London, Professor of Computational Linguistics at the University of Gothenburg and Emeritus Professor of Computational Linguistics at King’s College London.

Release date Australia

April 27th, 2021

Author

Shalom Lappin

Audiences

Professional & Vocational
Tertiary Education (US: College)

Illustrations

23 Tables, black and white; 55 Illustrations, black and white

Pages

168

Series

Chapman & Hall/CRC Machine Learning & Pattern Recognition

ISBN-13

9780367648749

Product ID

34023128

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