AI Superstream. MLOps.

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MLOps is consistently one of the greatest challenges engineers face when creating and maintaining machine learning systems. Join expert practitioners to learn techniques and best practices for operationalizing machine learning models and explore case studies of them in action, showing you what works...

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Bibliographic Details
Call Number:Libro Electrónico
Other Authors: Chang, Susan (Speaker), Tsubiks, Olga (Speaker), Gift, Noah (Speaker), Bell, Jason (Computer scientist) (Speaker), Zimmerman, Isabel (Speaker), Underwood, Todd (Computer scientist) (Speaker)
Format: Electronic Video
Language:Inglés
Published: Sebastopol, CA : O'Reilly Media, Inc., [2022]
Edition:[First edition].
Subjects:
Machine learning.
Instructional films.
Internet videos.
Nonfiction films.
Online Access:Texto completo (Requiere registro previo con correo institucional)
Table of Contents:
  • MLOps from good to great / Susan Shu Chang (19:25)
  • MLOps culture for continuous experimentation / Olga Tsubiks (27:58)
  • What can MLOps learn from the SRE mindset? / Noah Gift (30:47)
  • Deployment and metrics of machine learning models with Kubernetes and Prometheus / Jason Bell (32:51)
  • Composable tools for robust MLOps deployment / Isabel Zimmerman (29:33)
  • ML model quality as a reliability problem / Todd Underwood (29:56).

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