Natural Language Processing for Business and Organizations : Research and Innovation
Book Details
Format
Hardback or Cased Book
ISBN-10
1032657081
ISBN-13
9781032657080
Publisher
Taylor & Francis Ltd
Imprint
CRC Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jul 1st, 2026
Print length
194 Pages
Weight
540 grams
Product Classification:
Production & quality control managementProduction and quality control managementOperational researchErgonomicsElectrical engineeringAutomatic control engineeringCommunications engineering / telecommunicationsComputer-aided design (CAD)Data miningNatural language & machine translationNatural language and machine translation
Ksh 27,900.00
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This book offers a comprehensive and application-oriented exploration of Artificial Intelligence and Natural Language Processing (NLP), addressing both foundational principles and modern, data-driven methodologies.
This book offers a comprehensive and application-oriented exploration of Artificial Intelligence (AI) and Natural Language Processing (NLP), addressing both foundational principles and modern, data-driven methodologies. It is designed to equip readers with a deep understanding of how intelligent systems learn from data, interpret human language, and support automated decision-making across real-world contexts. Natural Language Processing for Business and Organizations: Research and Innovation covers key areas such as machine learning, deep learning, text representation, language modeling, information extraction, sentiment analysis, and AI-driven analytics, while also discussing system design considerations for deploying NLP solutions at scale. Through carefully structured chapters, the book integrates theoretical insights with practical examples, case studies, and applied workflows, enabling readers to translate algorithms and models into effective AI applications. Written by a team of academic researchers and industry practitioners, the book emphasizes responsible and value-driven AI, including ethical considerations, data quality, and model evaluation. This book is written for advanced undergraduate and postgraduate students, researchers, and professionals seeking to build, evaluate, and apply AI and NLP systems in academic, enterprise, and societal domains.
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