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Machine Learning and Deep Learning in Natural Language Processing
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Machine Learning and Deep Learning in Natural Language Processing

Book Details

Format Hardback or Cased Book
ISBN-10 1032264632
ISBN-13 9781032264639
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date Oct 18th, 2023
Print length 228 Pages
Weight 546 grams
Dimensions 16.00 x 24.30 x 1.90 cms
Ksh 18,900.00
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This book aims at providing a review of current Neural Network techniques in the NLP. The book is intended for a wide audience: beginners will find chapters providing a general introduction to the NLP techniques useful; experienced professionals would appreciate the chapters about advanced management of emotion etc.

Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of words, and then they utilize algorithms to extract meaning and produce results. Machine Learning and Deep Learning in Natural Language Processing aims at providing a review of current Neural Network techniques in the NLP field, in particular about Conversational Agents (chatbots), Text-to-Speech, management of non-literal content – like emotions, but also satirical expressions – and applications in the healthcare field.

NLP has the potential to be a disruptive technology in various healthcare fields, but so far little attention has been devoted to that goal. This book aims at providing some examples of NLP techniques that can, for example, restore speech, detect Parkinson’s disease, or help psychotherapists.

This book is intended for a wide audience. Beginners will find useful chapters providing a general introduction to NLP techniques, while experienced professionals will appreciate the chapters about advanced management of emotion, empathy, and non-literal content.


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