Item Infomation
Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Curtis, James | - |
| dc.contributor | Pandey, Parul | - |
| dc.contributor.author | Hall, Patrick | - |
| dc.date.accessioned | 2024-03-30T07:26:22Z | - |
| dc.date.available | 2024-03-30T07:26:22Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | http://thuvienso.thanglong.edu.vn//handle/TLU/9732 | - |
| dc.description.abstract | 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. | vi |
| dc.format.extent | 821ps | vi |
| dc.language.iso | en | vi |
| dc.publisher | O’Reilly Media, Inc | vi |
| dc.subject | Machine Learning | vi |
| dc.subject | Artificial Intelligence | vi |
| dc.subject | Trí tuệ nhân tạo | vi |
| dc.title | Machine Learning for High-Risk Applications: Approaches to Responsible AI | vi |
| dc.type | Sách/Book | vi |
| Appears in Collections | Tin học | |
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