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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: GreatBookPrices, Columbia, MD, U.S.A.
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EUR 43,21
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations (Paperback or Softback)
Lingua: Inglese
Editore: Packt Publishing 1/31/2024, 2024
ISBN 10: 1805120239 ISBN 13: 9781805120230
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
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Paperback or Softback. Condizione: New. MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations. Book.
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EUR 34,96
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Spedito da Germania a U.S.A.Quantità: 1 disponibili
Aggiungi al carrelloCondizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: California Books, Miami, FL, U.S.A.
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EUR 47,05
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 46,73
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Da: GreatBookPrices, Columbia, MD, U.S.A.
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EUR 51,47
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Da: California Books, Miami, FL, U.S.A.
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EUR 56,10
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Da: GreatBookPrices, Columbia, MD, U.S.A.
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EUR 54,69
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: Books Puddle, New York, NY, U.S.A.
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: Ria Christie Collections, Uxbridge, Regno Unito
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EUR 50,23
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Machine Learning on Kubernetes
Lingua: Inglese
Editore: Packt Publishing Limited, GB, 2022
ISBN 10: 1803241802 ISBN 13: 9781803241807
Da: Rarewaves.com USA, London, LONDO, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 66,09
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Aggiungi al carrelloPaperback. Condizione: New. Build a Kubernetes-based self-serving, agile data science and machine learning ecosystem for your organization using reliable and secure open source technologiesKey FeaturesBuild a complete machine learning platform on KubernetesImprove the agility and velocity of your team by adopting the self-service capabilities of the platformReduce time-to-market by automating data pipelines and model training and deploymentBook DescriptionMLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization.You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get hands-on experience in Kubernetes and open source tools, such as JupyterHub, MLflow, and Airflow.By the end of this book, you'll have learned how to effectively build, train, and deploy a machine learning model using the machine learning platform you built.What you will learnUnderstand the different stages of a machine learning projectUse open source software to build a machine learning platform on KubernetesImplement a complete ML project using the machine learning platform presented in this bookImprove on your organization s collaborative journey toward machine learningDiscover how to use the platform as a data engineer, ML engineer, or data scientistFind out how to apply machine learning to solve real business problemsWho this book is forThis book is for data scientists, data engineers, IT platform owners, AI product owners, and data architects who want to build their own platform for ML development. Although this book starts with the basics, a solid understanding of Python and Kubernetes, along with knowledge of the basic concepts of data science and data engineering will help you grasp the topics covered in this book in a better way.
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 50,22
Spedizione EUR 17,59
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
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Machine Learning on Kubernetes
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. pp. 347.
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 57,65
Spedizione EUR 14,05
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 53,78
Spedizione EUR 17,59
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Lingua: Inglese
Editore: Packt Publishing 2022-06-24, 2022
ISBN 10: 1803241802 ISBN 13: 9781803241807
Da: Chiron Media, Wallingford, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 54,14
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Aggiungi al carrelloPaperback. Condizione: New.
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 57,15
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Machine Learning on Kubernetes: A practical handbook for building and using a complete open source machine learning platform on Kubernetes
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 61,66
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Machine Learning on Kubernetes
Lingua: Inglese
Editore: Packt Publishing Limited, GB, 2022
ISBN 10: 1803241802 ISBN 13: 9781803241807
Da: Rarewaves.com UK, London, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 61,25
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Aggiungi al carrelloPaperback. Condizione: New. Build a Kubernetes-based self-serving, agile data science and machine learning ecosystem for your organization using reliable and secure open source technologiesKey FeaturesBuild a complete machine learning platform on KubernetesImprove the agility and velocity of your team by adopting the self-service capabilities of the platformReduce time-to-market by automating data pipelines and model training and deploymentBook DescriptionMLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization.You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get hands-on experience in Kubernetes and open source tools, such as JupyterHub, MLflow, and Airflow.By the end of this book, you'll have learned how to effectively build, train, and deploy a machine learning model using the machine learning platform you built.What you will learnUnderstand the different stages of a machine learning projectUse open source software to build a machine learning platform on KubernetesImplement a complete ML project using the machine learning platform presented in this bookImprove on your organization s collaborative journey toward machine learningDiscover how to use the platform as a data engineer, ML engineer, or data scientistFind out how to apply machine learning to solve real business problemsWho this book is forThis book is for data scientists, data engineers, IT platform owners, AI product owners, and data architects who want to build their own platform for ML development. Although this book starts with the basics, a solid understanding of Python and Kubernetes, along with knowledge of the basic concepts of data science and data engineering will help you grasp the topics covered in this book in a better way.
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MLOps with Red Hat OpenShift
Da: PBShop.store US, Wood Dale, IL, U.S.A.
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EUR 53,01
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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MLOps with Red Hat OpenShift
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
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EUR 50,71
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 4 su 5 stelle
EUR 54,63
Spedizione EUR 7,62
Spedito da Regno Unito a U.S.A.Quantità: 4 disponibili
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: Biblios, Frankfurt am main, HESSE, Germania
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EUR 54,60
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Spedito da Germania a U.S.A.Quantità: 4 disponibili
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Machine Learning on Kubernetes
Da: Majestic Books, Hounslow, Regno Unito
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EUR 64,16
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Aggiungi al carrelloCondizione: New. Print on Demand pp. 347.
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MLOps with Red Hat OpenShift: A cloud-native approach to machine learning operations
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
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EUR 56,92
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Aggiungi al carrelloPaperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
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Machine Learning on Kubernetes
Da: Biblios, Frankfurt am main, HESSE, Germania
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EUR 63,37
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EUR 66,84
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Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Über den AutorFaisal Masood is a cloud transformation architect at AWS. Faisal s focus is to assist customers in refining and executing strategic business goals. Faisal main interests are evolutionary architectures, software develop.
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EUR 58,80
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. MLOps with Red Hat OpenShift | A cloud-native approach to machine learning operations | Ross Brigoli (u. a.) | Taschenbuch | Englisch | 2024 | Packt Publishing | EAN 9781805120230 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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EUR 77,92
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build a Kubernetes-based self-serving, agile data science and machine learning ecosystem for your organization using reliable and secure open source technologiesKey Features:Build a complete machine learning platform on KubernetesImprove the agility and velocity of your team by adopting the self-service capabilities of the platformReduce time-to-market by automating data pipelines and model training and deploymentBook Description:MLOps is an emerging field that aims to bring repeatability, automation, and standardization of the software engineering domain to data science and machine learning engineering. By implementing MLOps with Kubernetes, data scientists, IT professionals, and data engineers can collaborate and build machine learning solutions that deliver business value for their organization.You'll begin by understanding the different components of a machine learning project. Then, you'll design and build a practical end-to-end machine learning project using open source software. As you progress, you'll understand the basics of MLOps and the value it can bring to machine learning projects. You will also gain experience in building, configuring, and using an open source, containerized machine learning platform. In later chapters, you will prepare data, build and deploy machine learning models, and automate workflow tasks using the same platform. Finally, the exercises in this book will help you get hands-on experience in Kubernetes and open source tools, such as JupyterHub, MLflow, and Airflow.By the end of this book, you'll have learned how to effectively build, train, and deploy a machine learning model using the machine learning platform you built.What You Will Learn:Understand the different stages of a machine learning projectUse open source software to build a machine learning platform on KubernetesImplement a complete ML project using the machine learning platform presented in this bookImprove on your organization's collaborative journey toward machine learningDiscover how to use the platform as a data engineer, ML engineer, or data scientistFind out how to apply machine learning to solve real business problemsWho this book is for:This book is for data scientists, data engineers, IT platform owners, AI product owners, and data architects who want to build their own platform for ML development. Although this book starts with the basics, a solid understanding of Python and Kubernetes, along with knowledge of the basic concepts of data science and data engineering will help you grasp the topics covered in this book in a better way.
