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9781098103019 - Practical MLOps: Operationalizing Machine Learning Models di Gift, Noah; Deza, Alfredo (35 risultati)
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Practical MLOps: Operationalizing Machine Learning Models
Lingua: Inglese
Editore: O'Reilly Media (edition 1), 2021
ISBN 10: 1098103017 ISBN 13: 9781098103019
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Paperback. Condizione: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Practical MLOps: Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models
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Practical MLOps : Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models
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Aggiungi al carrelloPaperback. Condizione: New. Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware.
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Practical MLOps
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Practical MLOps : Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models
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Practical MLOps (Paperback)
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2021
ISBN 10: 1098103017 ISBN 13: 9781098103019
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Practical MLOps : Operationalizing Machine Learning Models
Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Practical MLOps: Operationalizing Machine Learning Models (eng)
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Practical MLOps
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Aggiungi al carrelloPaperback. Condizione: New. Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware.
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Practical MLOps: Operationalizing Machine Learning Models
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Practical MLOps: Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
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Practical MLOps : Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models
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Practical MLOps: Operationalizing Machine Learning Models 1st Edition
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Practical Mlops: Operationalizing Machine Learning Models
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Practical MLOps
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Aggiungi al carrelloPaperback. Condizione: New. Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware.
-
Practical MLOps: Operationalizing Machine Learning Models 1st Edition
Da: Books Puddle, New York, NY, U.S.A.
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Practical MLOps (Paperback)
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2021
ISBN 10: 1098103017 ISBN 13: 9781098103019
Da: AussieBookSeller, Truganina, VIC, Australia
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Aggiungi al carrelloPaperback. Condizione: new. Paperback. Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.Current and aspiring machine learning engineers--or anyone familiar with data science and Python--will build a foundation in MLOps tools and methods (along with AutoML and monitoring and logging), then learn how to implement them in AWS, Microsoft Azure, and Google Cloud. The faster you deliver a machine learning system that works, the faster you can focus on the business problems you're trying to crack. This book gives you a head start.You'll discover how to:Apply DevOps best practices to machine learningBuild production machine learning systems and maintain themMonitor, instrument, load-test, and operationalize machine learning systemsChoose the correct MLOps tools for a given machine learning taskRun machine learning models on a variety of platforms and devices, including mobile phones and specialized hardware MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
