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Machine Learning for High-Risk Applications
Machine Learning for High-Risk Applications
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81,26 €
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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 competenci…
  • Leidėjas:
  • ISBN-10: 1098102436
  • ISBN-13: 9781098102432
  • Formatas: 17.6 x 23.2 x 2.8 cm, minkšti viršeliai
  • Kalba: Anglų

Machine Learning for High-Risk Applications (el. knyga) (skaityta knyga) | knygos.lt

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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 practice
  • Get a guide to existing standards, laws, and assessments for adopting AI technologies
  • Look at how existing roles at companies are evolving to incorporate responsible AI
  • Examine business best practices and recommendations for implementing responsible AI
  • Learn technical approaches for responsible AI at all stages of system development
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  • Autorius: Patrick Hall
  • Leidėjas:
  • ISBN-10: 1098102436
  • ISBN-13: 9781098102432
  • Formatas: 17.6 x 23.2 x 2.8 cm, minkšti viršeliai
  • Kalba: Anglų

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 practice
  • Get a guide to existing standards, laws, and assessments for adopting AI technologies
  • Look at how existing roles at companies are evolving to incorporate responsible AI
  • Examine business best practices and recommendations for implementing responsible AI
  • Learn technical approaches for responsible AI at all stages of system development

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