Artificial intelligence (AI) and machine learning (ML) have rapidly evolved from specialized research domains into transformative technologies that are reshaping nearly every aspect of modern society. Across industries, governments, healthcare systems, educational institutions, and research organizations, AI-driven solutions are increasingly being used to solve complex problems, improve decision-making, automate processes, and drive innovation. As these technologies continue to mature, their influence extends beyond technical efficiency, raising important questions about transparency, accountability, fairness, trustworthiness, and human oversight. As AI becomes embedded in critical sectors, successful implementation requires collaboration to develop systems that are transparent, inclusive, and responsive to human needs. Applied AI and Machine Learning for Real-World Systems explores the practical application of intelligent technologies while emphasizing the human dimensions that accompany their deployment. This book brings together contemporary research, innovative methodologies, emerging frameworks, and real-world case studies that demonstrate how AI and ML can be designed and implemented to address pressing challenges across multiple sectors. Covering topics such as open mapping, digital identity, and adaptive image encryption, this book is an indispensable academic resource for graduate and doctoral students, AI developers, software engineers, data scientists, technology practitioners, digital innovation professionals, policymakers, and more.
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Jingyuan Zhao obtained her PhD in Management Science and Engineering from University of Science and Technology of China. Dr. Zhao's research expertise includes management of technology innovation, behaviour and information technology, AI for industries, global innovation networks, high-tech industries, multinational governance, and science and technology policy. She has teaching experience of 15 years at the graduate and undergraduate level. Research portfolio includes peer-reviewed articles in highly regarded journals, authored books, multiple book chapters, and conference presentations. Dr. Zhao also has extensive industry experience and provides consulting services to major corporations such as China Mobile. She serves as editor-in-chief of International Journal of e-Collaboration (IJeC), a Scopus indexed journal.
V. Vinoth Kumar is an Associate Professor in the Department of Computer Science and Engineering in MVJ College of Engineering, Bangalore, India. He is a highly qualified individual with around 8 years of rich expertise in teaching, entrepreneurship, and research and development with specialization in computer science engineering subjects. He has been a part of various seminars, paper presentations, research paper reviews, and conferences as a convener and a session chair, a guest editor in journals and has co-authored several books and papers in national, international journals and conferences. He is a professional society member for ISTE, IACIST and IAENG. He has published more than 15 articles in National and International journals, 10 articles in conference proceedings and one article in book chapter. He has filed Indian patent in IoT Applications. His Research interest includes Mobile Adhoc Networking and IoT.
Joseph Richards joined the marketing faculty at CSUS in 2001. He holds a doctorate in Marketing with further specialization in Econometrics from Syracuse University. He is an active researcher in the fields of Internet related aspects of consumer behavior, marketing strategy, marketing analytics, and statistical and quantitative marketing models. Recent research and focus is in big data analytics. His publications have appeared in many leading journals.
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Paperback. Zustand: new. Paperback. Artificial intelligence (AI) and machine learning (ML) have rapidly evolved from specialized research domains into transformative technologies that are reshaping nearly every aspect of modern society. Across industries, governments, healthcare systems, educational institutions, and research organizations, AI-driven solutions are increasingly being used to solve complex problems, improve decision-making, automate processes, and drive innovation. As these technologies continue to mature, their influence extends beyond technical efficiency, raising important questions about transparency, accountability, fairness, trustworthiness, and human oversight. As AI becomes embedded in critical sectors, successful implementation requires collaboration to develop systems that are transparent, inclusive, and responsive to human needs. Applied AI and Machine Learning for Real-World Systems explores the practical application of intelligent technologies while emphasizing the human dimensions that accompany their deployment. This book brings together contemporary research, innovative methodologies, emerging frameworks, and real-world case studies that demonstrate how AI and ML can be designed and implemented to address pressing challenges across multiple sectors. Covering topics such as open mapping, digital identity, and adaptive image encryption, this book is an indispensable academic resource for graduate and doctoral students, AI developers, software engineers, data scientists, technology practitioners, digital innovation professionals, policymakers, and more. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798260027028
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Paperback. Zustand: new. Paperback. Artificial intelligence (AI) and machine learning (ML) have rapidly evolved from specialized research domains into transformative technologies that are reshaping nearly every aspect of modern society. Across industries, governments, healthcare systems, educational institutions, and research organizations, AI-driven solutions are increasingly being used to solve complex problems, improve decision-making, automate processes, and drive innovation. As these technologies continue to mature, their influence extends beyond technical efficiency, raising important questions about transparency, accountability, fairness, trustworthiness, and human oversight. As AI becomes embedded in critical sectors, successful implementation requires collaboration to develop systems that are transparent, inclusive, and responsive to human needs. Applied AI and Machine Learning for Real-World Systems explores the practical application of intelligent technologies while emphasizing the human dimensions that accompany their deployment. This book brings together contemporary research, innovative methodologies, emerging frameworks, and real-world case studies that demonstrate how AI and ML can be designed and implemented to address pressing challenges across multiple sectors. Covering topics such as open mapping, digital identity, and adaptive image encryption, this book is an indispensable academic resource for graduate and doctoral students, AI developers, software engineers, data scientists, technology practitioners, digital innovation professionals, policymakers, and more. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798260027028
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Paperback. Zustand: new. Paperback. Artificial intelligence (AI) and machine learning (ML) have rapidly evolved from specialized research domains into transformative technologies that are reshaping nearly every aspect of modern society. Across industries, governments, healthcare systems, educational institutions, and research organizations, AI-driven solutions are increasingly being used to solve complex problems, improve decision-making, automate processes, and drive innovation. As these technologies continue to mature, their influence extends beyond technical efficiency, raising important questions about transparency, accountability, fairness, trustworthiness, and human oversight. As AI becomes embedded in critical sectors, successful implementation requires collaboration to develop systems that are transparent, inclusive, and responsive to human needs. Applied AI and Machine Learning for Real-World Systems explores the practical application of intelligent technologies while emphasizing the human dimensions that accompany their deployment. This book brings together contemporary research, innovative methodologies, emerging frameworks, and real-world case studies that demonstrate how AI and ML can be designed and implemented to address pressing challenges across multiple sectors. Covering topics such as open mapping, digital identity, and adaptive image encryption, this book is an indispensable academic resource for graduate and doctoral students, AI developers, software engineers, data scientists, technology practitioners, digital innovation professionals, policymakers, and more. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9798260027028
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Taschenbuch. Zustand: Neu. Applied AI and Machine Learning for Real-World Systems | Jingyuan Zhao (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798260027028 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 136293110
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial intelligence (AI) and machine learning (ML) have rapidly evolved from specialized research domains into transformative technologies that are reshaping nearly every aspect of modern society. Across industries, governments, healthcare systems, educational institutions, and research organizations, AI-driven solutions are increasingly being used to solve complex problems, improve decision-making, automate processes, and drive innovation. As these technologies continue to mature, their influence extends beyond technical efficiency, raising important questions about transparency, accountability, fairness, trustworthiness, and human oversight. As AI becomes embedded in critical sectors, successful implementation requires collaboration to develop systems that are transparent, inclusive, and responsive to human needs. Applied AI and Machine Learning for Real-World Systems explores the practical application of intelligent technologies while emphasizing the human dimensions that accompany their deployment. This book brings together contemporary research, innovative methodologies, emerging frameworks, and real-world case studies that demonstrate how AI and ML can be designed and implemented to address pressing challenges across multiple sectors. Covering topics such as open mapping, digital identity, and adaptive image encryption, this book is an indispensable academic resource for graduate and doctoral students, AI developers, software engineers, data scientists, technology practitioners, digital innovation professionals, policymakers, and more. Bestandsnummer des Verkäufers 9798260027028
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