Machine Learning for High-Risk Applications: Approaches to Responsible AI
Hall, Patrick; Curtis, James; Pandey, Parul
ISBN 10: 1098102436 ISBN 13: 9781098102432
Editore: O'Reilly Media, 2023
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Codice articolo ABE-1681810708582
Riassunto:
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks.
This book describes approaches to responsible AI--a holistic framework 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. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public.
- Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security
- Learn how to create a successful and impactful AI risk management practice
- Get a basic guide to existing standards, laws, and assessments for adopting AI technologies, including the new NIST AI Risk Management Framework
- Engage with interactive resources on GitHub and Colab
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Titolo: Machine Learning for High-Risk Applications:...
Casa editrice: O'Reilly Media
Data di pubblicazione: 2023
Legatura: Soft cover
Condizione: New
Edizione: 1st Edition
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Machine Learning for High-Risk Applications
Editore:
O'Reilly Media, US, 2023
ISBN 10: 1098102436
ISBN 13: 9781098102432
Nuovo
Paperback
Prima edizione
Da: Rarewaves USA, OSWEGO, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: 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. Codice articolo LU-9781098102432
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Machine Learning for High-Risk Applications
Editore:
O'Reilly Media, US, 2023
ISBN 10: 1098102436
ISBN 13: 9781098102432
Nuovo
Paperback
Prima edizione
Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: 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. Codice articolo LU-9781098102432
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Machine Learning for High-Risk Applications
Editore:
O'Reilly Media, US, 2023
ISBN 10: 1098102436
ISBN 13: 9781098102432
Nuovo
Paperback
Prima edizione
Da: Rarewaves.com UK, London, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: 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. Codice articolo LU-9781098102432
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Machine Learning for High-Risk Applications
Editore:
O'Reilly Media, US, 2023
ISBN 10: 1098102436
ISBN 13: 9781098102432
Nuovo
Paperback
Prima edizione
Da: Rarewaves.com USA, London, LONDO, Regno Unito
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: 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. Codice articolo LU-9781098102432
Quantità: Più di 20 disponibili