Practicing Trustworthy Machine Learning consistent, transparent, and fair AI pipelines

With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and m...

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Bibliographische Detailangaben

Hauptverfasser:	Pruksachatkun, Yada (VerfasserIn), McAteer, Matthew (VerfasserIn), Majumdar, Subhabrata (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Beijing ; Boston ; Farnham ; Sebastopol ; Tokyo O'Reilly Media, Inc. ©2023
Ausgabe:	1st edition
Schlagworte:	Electronic books
Online-Zugang:	UER01
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