Artificial intelligence theory, models, and applications / edited by P. Kaliraj, and T. Devi
Material type: TextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2022Copyright date: ©2022Description: xxv, 479 pages : illustrations ; 24 cmContent type:- text
- unmediated
- volume
- 9781032008097 (hardback)
- Q335 A78
Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
General Q-R (Science & Medicine)- 1st floor | Universiti Islam Sultan Sharif Ali First Floor (Gadong Campus) | Q335.A787 2022 c.1 (Browse shelf(Opens below)) | 1 | Available | 1050069750 |
Includes bibliographical references and index.
This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills.
Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world --
A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization --
The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine --
AI’s role in the diagnosis of various diseases, such as cancer and diabetes
The role of machine learning models in product development and statistically monitoring product quality
Machine learning to make robust and effective economic policy decisions
Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results
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