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Machine learning for high-risk applications : approaches to responsible AI /
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...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , , |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Sebastopol, CA :
O'Reilly Media, Inc.,
2023.
|
| Edición: | [First edition]. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 049 | |a UAMI | ||
| 100 | 1 | |a Hall, Patrick, |e author. | |
| 245 | 1 | 0 | |a Machine learning for high-risk applications : |b approaches to responsible AI / |c Patrick Hall, James Curtis, and Parul Pandey ; foreword by Agus Sudjianto. |
| 250 | |a [First edition]. | ||
| 264 | 1 | |a Sebastopol, CA : |b O'Reilly Media, Inc., |c 2023. | |
| 300 | |a 1 online resource (466 pages) : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 500 | |a Includes index. | ||
| 520 | |a 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. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Machine learning. | |
| 650 | 0 | |a Risk management. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 6 | |a Gestion du risque. | |
| 650 | 6 | |a Intelligence artificielle. | |
| 650 | 7 | |a risk management. |2 aat | |
| 650 | 7 | |a artificial intelligence. |2 aat | |
| 650 | 7 | |a Artificial intelligence |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 650 | 7 | |a Risk management |2 fast | |
| 700 | 1 | |a Curtis, James, |e author. | |
| 700 | 1 | |a Pandey, Parul, |e author. | |
| 700 | 1 | |a Sudjianto, Agus, |e writer of foreword. | |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781098102425/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 938 | |a EBSCOhost |b EBSC |n 3594186 | ||
| 994 | |a 92 |b IZTAP | ||