Articoli correlati a Machine Learning for High-Risk Applications: Approaches...
- EditoreO'Reilly Media
- Data di pubblicazione2023
- ISBN 10 1098102436
- ISBN 13 9781098102432
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero edizione1
- Numero di pagine466
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Machine Learning for HighRisk
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Machine Learning for High-risk Applications : Approaches to Responsible Ai
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Machine Learning for High-Risk Applications: Approaches to Responsible AI (Paperback or Softback)
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O'Reilly Media 5/23/2023, 2023
ISBN 10: 1098102436
ISBN 13: 9781098102432
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Paperback or Softback. Condizione: New. Machine Learning for High-Risk Applications: Approaches to Responsible AI 1.64. Book. Codice articolo BBS-9781098102432
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Machine Learning for High-Risk Applications: Approaches to Responsible AI [Paperback] Hall, Patrick; Curtis, James and Pandey, Parul
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Machine Learning for High-risk Applications : Approaches to Responsible Ai
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Machine Learning for High-Risk Applications (Paperback)
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O'Reilly Media, Sebastopol, 2023
ISBN 10: 1098102436
ISBN 13: 9781098102432
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Paperback. Condizione: new. Paperback. 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 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781098102432
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Machine Learning for High-risk Applications : Approaches to Responsible Ai
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Machine Learning for High-Risk Applications: Techniques for Responsible AI
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Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days. 209. Codice articolo B9781098102432
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