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Practical Mlops

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Description: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 hardwareWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Practical Mlops. To get started finding Practical Mlops, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 460

Format: PDF, EPUB & Kindle Edition

Publisher: O'Reilly Media

Release: 2021

ISBN: 1098102983

Description: 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 hardwareWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Practical Mlops. To get started finding Practical Mlops, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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