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Learning Ray flexible distributed Python for machine learning

Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You&...

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Bibliographic Details
Main Authors: Pumperla, Max, Oakes, Edward (Author), Liaw, Richard (Author)
Format: eBook
Language:English
Published: Sebastopol, California O'Reilly Media, Inc. 2023
Edition:Frist edtion
Subjects:
Traitement Réparti
Machine Learning / Http://id.loc.gov/authorities/subjects/sh85079324
Python (computer Program Language) / Fast
Python (computer Program Language) / Http://id.loc.gov/authorities/subjects/sh96008834
Application Program Interfaces (computer Software) / Http://id.loc.gov/authorities/subjects/sh98004527
Electronic Data Processing / Distributed Processing / Fast
Artificial Intelligence / Fast
Apis (interfaces) / Aat
Artificial Intelligence / Http://id.loc.gov/authorities/subjects/sh85008180
Electronic Data Processing / Distributed Processing / Http://id.loc.gov/authorities/subjects/sh85042293
Intelligence Artificielle
Application Program Interfaces (computer Software) / Fast
Machine Learning / Fast
Apprentissage Automatique
Artificial Intelligence / Aat
Interfaces De Programmation D'applications
Python (langage De Programmation)
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Description
Summary:Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine learning programs at scale
Physical Description:1 online resource
ISBN:9781098117191

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