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Añadir al carritopaperback. Condición: Very Good. Shipped within 24 hours from our UK warehouse. Clean, undamaged book with no damage to pages and minimal wear to the cover. Spine still tight, in very good condition. Remember if you are not happy, you are covered by our 100% money back guarantee.
Librería: AwesomeBooks, Wallingford, Reino Unido
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Añadir al carritopaperback. Condición: Very Good. Continuous Machine Learning with Kubeflow: Performing Reliable MLOps with Capabilities of TFX, Sagemaker and Kubernetes (English Edition) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
Librería: ThriftBooks-Atlanta, AUSTELL, GA, Estados Unidos de America
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Añadir al carritoPaperback. Condición: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less 1.25.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 37,78
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Publicado por Bpb Publications 11/20/2021, 2021
ISBN 10: 9389898501 ISBN 13: 9789389898507
Idioma: Inglés
Librería: BargainBookStores, Grand Rapids, MI, Estados Unidos de America
EUR 40,21
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Añadir al carritoPaperback or Softback. Condición: New. Continuous Machine Learning with Kubeflow: Performing Reliable MLOps with Capabilities of TFX, Sagemaker and Kubernetes (English Edition) 1.25. Book.
Publicado por BPB Publications 2021-11, 2021
ISBN 10: 9389898501 ISBN 13: 9789389898507
Idioma: Inglés
Librería: Chiron Media, Wallingford, Reino Unido
EUR 35,25
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 40,07
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Librería: Best Price, Torrance, CA, Estados Unidos de America
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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EUR 44,20
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Publicado por BPB Publications (edition ), 2021
ISBN 10: 9389898501 ISBN 13: 9789389898507
Idioma: Inglés
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
EUR 13,73
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Añadir al carritoPaperback. Condición: Very Good. 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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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.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 54,84
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An insightful journey to MLOps, DevOps, and Machine Learning in the real environment. KEY FEATURES ¿ Extensive knowledge and concept explanation of Kubernetes components with examples. ¿ An all-in-one knowledge guide to train and deploy ML pipelines using Docker and Kubernetes. ¿ Includes numerous MLOps projects with access to proven frameworks and the use of deep learning concepts. DESCRIPTION 'Continuous Machine Learning with Kubeflow' introduces you to the modern machine learning infrastructure, which includes Kubernetes and the Kubeflow architecture. This book will explain the fundamentals of deploying various AI/ML use cases with TensorFlow training and serving with Kubernetes and how Kubernetes can help with specific projects from start to finish. This book will help demonstrate how to use Kubeflow components, deploy them in GCP, and serve them in production using real-time data prediction. With Kubeflow KFserving, we'll look at serving techniques, build a computer vision-based user interface in streamlit, and then deploy it to the Google cloud platforms, Kubernetes and Heroku. Next, we also explore how to build Explainable AI for determining fairness and biasness with a What-if tool. Backed with various use-cases, we will learn how to put machine learning into production, including training and serving. WHAT YOU WILL LEARN ¿ Get comfortable with the architecture and the orchestration of Kubernetes. ¿ Learn to containerize and deploy from scratch using Docker and Google Cloud Platform. ¿ Practice how to develop the Kubeflow Orchestrator pipeline for a TensorFlow model. ¿ Create AWS SageMaker pipelines, right from training to deployment in production. ¿ Build the TensorFlow Extended (TFX) pipeline for an NLP application using Tensorboard and TFMA. WHO THIS BOOK IS FOR This book is for MLOps, DevOps, Machine Learning Engineers, and Data Scientists who want to continuously deploy machine learning pipelines and manage them at scale using Kubernetes. The readers should have a strong background in machine learning and some knowledge of Kubernetes is required.