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ML Ops : Operationalizing Data Science /

More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Instead, many of these ML models do nothing more than provide static insights in a slideshow. If they aren't truly operational, these models can't possibly do what...

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Detalles Bibliográficos
Autores principales: Sweenor, David (Autor), Hillion, Steven (Autor), Rope, Dan (Autor), Kannabiran, Dev (Autor), Hill, Thomas (Autor), O'Connell, Michael (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico eBook
Idioma:Inglés
Publicado: O'Reilly Media, Inc., 2020.
Edición:1st edition.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

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