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Machine Learning for High-Risk Applications: Approaches to Responsible AI
Published by O'Reilly Media (edition 1), 2023
ISBN 10: 1098102436 ISBN 13: 9781098102432
Language: English
£ 28.26
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Add to basketPaperback. Condition: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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Machine Learning for High-Risk Applications : Approaches to Responsible AI
Published by O'Reilly Media, Incorporated, 2023
ISBN 10: 1098102436 ISBN 13: 9781098102432
Language: English
£ 36.39
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Add to basketCondition: Good. Used book that is in clean, average condition without any missing pages.
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Machine Learning for High-risk Applications : Approaches to Responsible Ai
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Machine Learning for High-risk Applications : Approaches to Responsible Ai
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Machine Learning for High-Risk Applications: Approaches to Responsible AI
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Machine Learning for High-Risk Applications
First Edition
£ 53.62
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Add to basketPaperback. Condition: New. 1st. The past decade has witnessed a wide adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight into their widespread implementation has resulted in harmful outcomes that could have been avoided with proper oversight. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes responsible AI, a holistic approach for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science.It's an ambitious undertaking that requires a diverse set of talents, experiences, and perspectives. Data scientists and nontechnical oversight folks alike need to be recruited and empowered to audit and evaluate high-impact AI/ML systems. Author Patrick Hall created this guide for a new generation of auditors and assessors who want to make AI systems better for organizations, consumers, and the public at large.Learn how to create a successful and impactful responsible AI practiceGet a guide to existing standards, laws, and assessments for adopting AI technologiesLook at how existing roles at companies are evolving to incorporate responsible AIExamine business best practices and recommendations for implementing responsible AILearn technical approaches for responsible AI at all stages of system development.
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£ 30.18
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£ 30.18
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£ 42.59
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£ 49.49
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Add to basketCondition: As New. Unread book in perfect condition.
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Machine Learning for High-Risk Applications
First Edition
Paperback. Condition: New. 1st. The past decade has witnessed a wide adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight into their widespread implementation has resulted in harmful outcomes that could have been avoided with proper oversight. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes responsible AI, a holistic approach for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science.It's an ambitious undertaking that requires a diverse set of talents, experiences, and perspectives. Data scientists and nontechnical oversight folks alike need to be recruited and empowered to audit and evaluate high-impact AI/ML systems. Author Patrick Hall created this guide for a new generation of auditors and assessors who want to make AI systems better for organizations, consumers, and the public at large.Learn how to create a successful and impactful responsible AI practiceGet a guide to existing standards, laws, and assessments for adopting AI technologiesLook at how existing roles at companies are evolving to incorporate responsible AIExamine business best practices and recommendations for implementing responsible AILearn technical approaches for responsible AI at all stages of system development.
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Condition: New.
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Machine Learning for High-risk Applications: Techniques for Responsible Ai
Published by Oreilly & Associates Inc, 2023
ISBN 10: 1098102436 ISBN 13: 9781098102432
Language: English
Paperback. Condition: Brand New. 350 pages. 9.19x7.00x0.95 inches. In Stock.
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£ 55.88
Convert currency£ 21.71 shipping from Germany to United KingdomQuantity: 3 available
Add to basketKartoniert / Broschiert. Condition: New. Über den AutorPatrick Hall is principal scientist at BNH.AI, where he advises Fortune 500 companies and cutting-edge startups on AI risk and conducts research in support of NIST s AI risk management framework. He also serves as v.
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£ 81.09
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£ 88.52
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Machine Learning for High-Risk Applications
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
First Edition
Paperback. Condition: New. 1st. The past decade has witnessed a wide adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight into their widespread implementation has resulted in harmful outcomes that could have been avoided with proper oversight. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes responsible AI, a holistic approach for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science.It's an ambitious undertaking that requires a diverse set of talents, experiences, and perspectives. Data scientists and nontechnical oversight folks alike need to be recruited and empowered to audit and evaluate high-impact AI/ML systems. Author Patrick Hall created this guide for a new generation of auditors and assessors who want to make AI systems better for organizations, consumers, and the public at large.Learn how to create a successful and impactful responsible AI practiceGet a guide to existing standards, laws, and assessments for adopting AI technologiesLook at how existing roles at companies are evolving to incorporate responsible AIExamine business best practices and recommendations for implementing responsible AILearn technical approaches for responsible AI at all stages of system development.
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£ 69.03
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Add to basketSoft cover. Condition: New. 1st Edition.
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Machine Learning for High-Risk Applications
First Edition
£ 53.90
Convert currency£ 85.64 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketPaperback. Condition: New. 1st. The past decade has witnessed a wide adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight into their widespread implementation has resulted in harmful outcomes that could have been avoided with proper oversight. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes responsible AI, a holistic approach for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science.It's an ambitious undertaking that requires a diverse set of talents, experiences, and perspectives. Data scientists and nontechnical oversight folks alike need to be recruited and empowered to audit and evaluate high-impact AI/ML systems. Author Patrick Hall created this guide for a new generation of auditors and assessors who want to make AI systems better for organizations, consumers, and the public at large.Learn how to create a successful and impactful responsible AI practiceGet a guide to existing standards, laws, and assessments for adopting AI technologiesLook at how existing roles at companies are evolving to incorporate responsible AIExamine business best practices and recommendations for implementing responsible AILearn technical approaches for responsible AI at all stages of system development.
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Machine Learning for High-risk Applications: Techniques for Responsible Ai
Published by Oreilly & Associates Inc, 2023
ISBN 10: 1098102436 ISBN 13: 9781098102432
Language: English
Paperback. Condition: Brand New. 350 pages. 9.19x7.00x0.95 inches. In Stock. This item is printed on demand.
