Pluralsight.Operational.Considerations.for.AI.and.ML.Workloads.for.Azure.2026.BOOKWARE-GETH

Section
eBooks/Audiobooks
Group
GETH
Size
140,98 MB
Files
5
Date
2026-08-25

NFO

        Publisher > Pluralsight
            Title > Operational Considerations for AI and ML
                    Workloads for Azure
           Author > Zachary Bennett
          Modules > 4
            Clips > 12
         Duration > 00:53:31
        Published > 2026-08-24
         Released > 2026-08-25
            Files > 03*50MB
         Language > English
        Subtitles > English
      Description > AI workloads fail silently: quality drifts,
                    costs spike, guardrails gap. This course will
                    teach you how to operate production AI
                    workloads on Azure by integrating evaluation,
                    guardrail, and monitoring signals into your
                    existing ops stack.
              Url > https://www.pluralsight.com/courses/azure-ai-m
                    l-workloads-operational
            Notes > --

Files

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