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Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
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Add to basketCondition: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
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Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
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Deploy Machine Learning Models to Production : With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
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Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
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Deploy Machine Learning Models to Production : With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform
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Condition: New. 1st ed. edition NO-PA16APR2015-KAP.
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Deploy Machine Learning Models to Production
Published by Apress, Apress Dez 2020, 2020
ISBN 10: 1484265459 ISBN 13: 9781484265451
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Add to basketTaschenbuch. Condition: Neu. Neuware -Build and deploy machine learning and deep learning models in production with end-to-end examples.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 164 pp. Englisch.
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Add to basketTaschenbuch. Condition: Neu. Deploy Machine Learning Models to Production | With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform | Pramod Singh | Taschenbuch | xiii | Englisch | 2020 | APRESS | EAN 9781484265451 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Deploy Machine Learning Models to Production
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Build and deploy machine learning and deep learning models in production with end-to-end examples.This book begins with a focus on the machine learning model deployment process and its related challenges. Next, it covers the process of building and deploying machine learning models using different web frameworks such as Flask and Streamlit. A chapter on Docker follows and covers how to package and containerize machine learning models. The book also illustrates how to build and train machine learning and deep learning models at scale using Kubernetes.The book is a good starting point for people who want to move to the next level of machine learning by taking pre-built models and deploying them into production. It also offers guidance to those who want to move beyond Jupyter not Elektronisches Buch to training models at scale on cloud environments. All the code presented in the book is available in the form of Python scripts for you to try the examples and extend them in interesting ways.What You Will LearnBuild, train, and deploy machine learning models at scale using KubernetesContainerize any kind of machine learning model and run it on any platform using DockerDeploy machine learning and deep learning models using Flask and Streamlit frameworksWho This Book Is ForData engineers, data scientists, analysts, and machine learning and deep learning engineers 164 pp. Englisch.
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Add to basketCondition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Intermediate-Advanced user level|Guides you in transitioning from traditional machine learning to machine learning productionizationCovers the entire range of deployment options, including Flask, Streamlit, Docker, and Kubernetes .
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build and deploy machine learning and deep learning models in production with end-to-end examples.This book begins with a focus on the machine learning model deployment process and its related challenges. Next, it covers the process of building and deploying machine learning models using different web frameworks such as Flask and Streamlit. A chapter on Docker follows and covers how to package and containerize machine learning models. The book also illustrates how to build and train machine learning and deep learning models at scale using Kubernetes.The book is a good starting point for people who want to move to the next level of machine learning by taking pre-built models and deploying them into production. It also offers guidance to those who want to move beyond Jupyter not Elektronisches Buch to training models at scale on cloud environments. All the code presented in the book is available in the form of Python scripts for you to try the examples and extend them in interesting ways.What You Will LearnBuild, train, and deploy machine learning models at scale using KubernetesContainerize any kind of machine learning model and run it on any platform using DockerDeploy machine learning and deep learning models using Flask and Streamlit frameworksWho This Book Is ForData engineers, data scientists, analysts, and machine learning and deep learning engineers.
