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Ajouter au panierPaperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.24.
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
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Ajouter au panierEtat : New. In.
Edité par Packt Publishing 2022-03, 2022
ISBN 10 : 1801070156 ISBN 13 : 9781801070157
Langue: anglais
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Ajouter au panierEtat : New.
Edité par Packt Publishing 3/31/2022, 2022
ISBN 10 : 1801070156 ISBN 13 : 9781801070157
Langue: anglais
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Ajouter au panierPaperback or Softback. Etat : New. Getting Started with Amazon SageMaker Studio: Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE 1.24. Book.
Edité par Packt Publishing Limited, 2022
ISBN 10 : 1801070156 ISBN 13 : 9781801070157
Langue: anglais
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
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Ajouter au panierPAP. Etat : New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Packt Publishing Limited, 2022
ISBN 10 : 1801070156 ISBN 13 : 9781801070157
Langue: anglais
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Ajouter au panierPAP. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Edité par Packt Publishing Limited, 2022
ISBN 10 : 1801070156 ISBN 13 : 9781801070157
Langue: anglais
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
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Ajouter au panierPaperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 100.
Edité par Packt Publishing, Limited, 2022
ISBN 10 : 1801070156 ISBN 13 : 9781801070157
Langue: anglais
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Ajouter au panierEtat : New. Print on Demand pp. 326.
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Ajouter au panierEtat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Developers working with machine learning will be able to put their knowledge to work with this practical guide to Amazon SageMaker Studio. The book takes a hands-on approach to implementing real-world machine learning use cases that will have you up and run.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build production-grade machine learning models with Amazon SageMaker Studio, the first integrated development environment in the cloud, using real-life machine learning examples and code Key Features:Understand the ML lifecycle in the cloud and its development on Amazon SageMaker Studio Learn to apply SageMaker features in SageMaker Studio for ML use cases Scale and operationalize the ML lifecycle effectively using SageMaker Studio Book Description: Amazon SageMaker Studio is the first integrated development environment (IDE) for machine learning (ML) and is designed to integrate ML workflows: data preparation, feature engineering, statistical bias detection, automated machine learning (AutoML), training, hosting, ML explainability, monitoring, and MLOps in one environment. In this book, you'll start by exploring the features available in Amazon SageMaker Studio to analyze data, develop ML models, and productionize models to meet your goals. As you progress, you will learn how these features work together to address common challenges when building ML models in production. After that, you'll understand how to effectively scale and operationalize the ML life cycle using SageMaker Studio. By the end of this book, you'll have learned ML best practices regarding Amazon SageMaker Studio, as well as being able to improve productivity in the ML development life cycle and build and deploy models easily for your ML use cases. What You Will Learn:Explore the ML development life cycle in the cloud Understand SageMaker Studio features and the user interface Build a dataset with clicks and host a feature store for ML Train ML models with ease and scale Create ML models and solutions with little code Host ML models in the cloud with optimal cloud resources Ensure optimal model performance with model monitoring Apply governance and operational excellence to ML projects Who this book is for: This book is for data scientists and machine learning engineers who are looking to become well-versed with Amazon SageMaker Studio and gain hands-on machine learning experience to handle every step in the ML lifecycle, including building data as well as training and hosting models. Although basic knowledge of machine learning and data science is necessary, no previous knowledge of SageMaker Studio and cloud experience is required.