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Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6203854735 ISBN 13: 9786203854732
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Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6203854735 ISBN 13: 9786203854732
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Language: Spanish
Published by Ediciones Nuestro Conocimiento, 2023
ISBN 10: 6206872696 ISBN 13: 9786206872696
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Published by LAP LAMBERT Academic Publishing, 2022
ISBN 10: 6203854735 ISBN 13: 9786203854732
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Taschenbuch. Condition: Neu. Integration of Renewable Energy Sources Using Matrix Converter | Karthick Kumar K. (u. a.) | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786203854732 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Published by Editions Notre Savoir, 2023
ISBN 10: 6206872688 ISBN 13: 9786206872689
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Language: English
Published by John Wiley & Sons Inc, New York, 2026
ISBN 10: 1394392990 ISBN 13: 9781394392995
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Hardcover. Condition: new. Hardcover. For industry practitioners, academic researchers, and governance professionals alike, this book offers both clarity and depth in one of the most important domains of modern technology. As AI matures, trust and risk management will define its successand this book lays the groundwork for achieving that vision. As AI continues to permeate sectors ranging from healthcare to finance, ensuring that these systems are not only powerful but also accountable, transparent, and secure, is more critical than ever. This book offers a vital exploration into the intersection of trustworthiness, risk mitigation, and security governance in artificial intelligence systems, serving as a definitive guide for professionals, researchers, and policymakers striving to build, deploy, and manage AI responsibly in high-stakes environments. Using a comprehensive approach, it explores how to integrate technical safeguards, organizational practices, and regulatory alignment to manage the unique risks posed by AI, including algorithmic bias, data misuse, adversarial attacks, and opaque decision-making. The result is a strategic approach that not only identifies vulnerabilities, but also promotes resilient, auditable, and trustworthy AI ecosystems. At its core, AI TRiSM is a forward-looking concept that embraces the realities of AI in production environments. The framework moves beyond traditional static models of governance to propose dynamic, adaptive controls that evolve alongside AI systems. Through real-world case studies, the book outlines how tools like model cards, bias audits, and zero-trust architectures can be embedded into the AI development lifecycle. Readers will find the volume: Introduces concepts to stay ahead of regulations and build trustworthy AI systems that customers and stakeholders can rely on;Addresses security threats, bias, and compliance gaps to avoid costly AI failures;Explores proven frameworks and best practices to deploy AI responsibly and strategies to outperform;Provides comprehensive guidance through real-world case studies and contributions from industry and academia. Audience AI and machine learning engineers, data scientists, cybersecurity and risk management specialists, academics, researchers, and policymakers specializing in AI ethics, security, and risk management. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Apple Academic Press, 2025
ISBN 10: 1774919729 ISBN 13: 9781774919729
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Published by Apple Academic Press, 2025
ISBN 10: 1774919729 ISBN 13: 9781774919729
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Published by Apple Academic Press, 2025
ISBN 10: 1774919729 ISBN 13: 9781774919729
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Published by Apple Academic Press, 2025
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Published by Apple Academic Press, 2025
ISBN 10: 1774919729 ISBN 13: 9781774919729
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Published by Apple Academic Press, 2025
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Published by Apple Academic Press, 2025
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Language: English
Published by John Wiley & Sons Inc Feb 2026, 2026
ISBN 10: 1394392990 ISBN 13: 9781394392995
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Buch. Condition: Neu. Neuware - For industry practitioners, academic researchers, and governance professionals alike, this book offers both clarity and depth in one of the most important domains of modern technology. As AI matures, trust and risk management will define its success-and this book lays the groundwork for achieving that vision. As AI continues to permeate sectors ranging from healthcare to finance, ensuring that these systems are not only powerful but also accountable, transparent, and secure, is more critical than ever. This book offers a vital exploration into the intersection of trustworthiness, risk mitigation, and security governance in artificial intelligence systems, serving as a definitive guide for professionals, researchers, and policymakers striving to build, deploy, and manage AI responsibly in high-stakes environments. Using a comprehensive approach, it explores how to integrate technical safeguards, organizational practices, and regulatory alignment to manage the unique risks posed by AI, including algorithmic bias, data misuse, adversarial attacks, and opaque decision-making. The result is a strategic approach that not only identifies vulnerabilities, but also promotes resilient, auditable, and trustworthy AI ecosystems. At its core, AI TRiSM is a forward-looking concept that embraces the realities of AI in production environments. The framework moves beyond traditional static models of governance to propose dynamic, adaptive controls that evolve alongside AI systems. Through real-world case studies, the book outlines how tools like model cards, bias audits, and zero-trust architectures can be embedded into the AI development lifecycle. Readers will find the volume: - Introduces concepts to stay ahead of regulations and build trustworthy AI systems that customers and stakeholders can rely on;- Addresses security threats, bias, and compliance gaps to avoid costly AI failures;- Explores proven frameworks and best practices to deploy AI responsibly and strategies to outperform;- Provides comprehensive guidance through real-world case studies and contributions from industry and academia. Audience AI and machine learning engineers, data scientists, cybersecurity and risk management specialists, academics, researchers, and policymakers specializing in AI ethics, security, and risk management.
Language: English
Published by Apple Academic Press, 2025
ISBN 10: 1774919729 ISBN 13: 9781774919729
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