AI Superstream. MLOps

AI Superstream MLOps MLOps.

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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Detalles Bibliográficos
Autor Corporativo: O'Reilly (Firm), publisher (publisher)
Otros Autores: Manjengwa, Shingai. host (host), Chang, Susan. speaker (speaker), Tsubiks, Olga. speaker, Gift, Noah. speaker, Bell, Jason (Computer scientist), speaker, Zimmerman, Isabel. speaker, Underwood, Todd (Computer scientist), speaker
Formato: Video
Idioma:Inglés
Publicado: Sebastopol, CA : O'Reilly Media, Inc [2022]
Edición:[First edition]
Materias:
Machine learning.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009825863706719
Tabla de Contenidos:
  • 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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