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Añadir al carritopaperback. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Añadir al carritopaperback. Condición: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority!
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Publicado por Packt Publishing 10/22/2021, 2021
ISBN 10: 1800567030 ISBN 13: 9781800567030
Idioma: Inglés
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Añadir al carritoPaperback or Softback. Condición: New. Machine Learning with Amazon SageMaker Cookbook: 80 proven recipes for data scientists and developers to perform machine learning experiments and depl 2.83. Book.
Librería: California Books, Miami, FL, Estados Unidos de America
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Publicado por Packt Publishing 2021-10, 2021
ISBN 10: 1800567030 ISBN 13: 9781800567030
Idioma: Inglés
Librería: Chiron Media, Wallingford, Reino Unido
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Añadir al carritoCondición: New. Explore the capabilities of Amazon SageMaker to effectively train, deploy, and manage machine learning and deep learning models in AWS with complete and thoroughly explained hands-on examples. With 80 proven recipes, this step-by-step guide will help you bu.
Publicado por Packt Publishing Limited, 2021
ISBN 10: 1800567030 ISBN 13: 9781800567030
Idioma: Inglés
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por Packt Publishing Limited, 2021
ISBN 10: 1800567030 ISBN 13: 9781800567030
Idioma: Inglés
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Publicado por Packt Publishing Limited, 2021
ISBN 10: 1800567030 ISBN 13: 9781800567030
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Publicado por Packt Publishing, Limited, 2021
ISBN 10: 1800567030 ISBN 13: 9781800567030
Idioma: Inglés
Librería: Majestic Books, Hounslow, Reino Unido
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Añadir al carritoCondición: New. Print on Demand pp. 762.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key Features:Perform ML experiments with built-in and custom algorithms in SageMaker Explore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn Use the different features and capabilities of SageMaker to automate relevant ML processes Book Description: Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams. By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems. What You Will Learn:Train and deploy NLP, time series forecasting, and computer vision models to solve different business problems Push the limits of customization in SageMaker using custom container images Use AutoML capabilities with SageMaker Autopilot to create high-quality models Work with effective data analysis and preparation techniques Explore solutions for debugging and managing ML experiments and deployments Deal with bias detection and ML explainability requirements using SageMaker Clarify Automate intermediate and complex deployments and workflows using a variety of solutions Who this book is for: This book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.