Da: ThriftBooks-Dallas, Dallas, TX, U.S.A.
EUR 35,79
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Aggiungi al carrelloPaperback. Condizione: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.85.
EUR 44,89
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Da: California Books, Miami, FL, U.S.A.
EUR 47,30
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 43,80
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Editore: Packt Publishing 4/30/2020, 2020
ISBN 10: 1789807557 ISBN 13: 9781789807554
Lingua: Inglese
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
EUR 48,38
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Aggiungi al carrelloPaperback or Softback. Condizione: New. Mastering Azure Machine Learning 1.49. Book.
EUR 52,54
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Da: Russell Books, Victoria, BC, Canada
EUR 53,47
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Da: Chiron Media, Wallingford, Regno Unito
EUR 45,02
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 50,24
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EUR 54,81
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Da: Studibuch, Stuttgart, Germania
EUR 29,57
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Aggiungi al carrellopaperback. Condizione: Gut. 436 Seiten; 9781789807554.3 Gewicht in Gramm: 1.
EUR 55,44
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Aggiungi al carrelloCondizione: New. This book will help you learn how to build a scalable end-to-end machine learning pipeline in Azure from experimentation and training to optimization and deployment. By the end of this book, you will learn to build complex distributed systems and scalable c.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 81,19
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Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 69,83
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and KubernetesKey FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book DescriptionThe increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud.The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure ML and takes you through the process of data experimentation, data preparation, and feature engineering using Azure ML and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure AutoML and HyperDrive, and perform distributed training on Azure ML. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure ML, along with the basics of MLOps-DevOps for ML to automate your ML process as CI/CD pipeline.By the end of this book, you'll have mastered Azure ML and be able to confidently design, build and operate scalable ML pipelines in Azure.What you will learnSetup your Azure ML workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure MLUse hyperparameter tuning and AutoML to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure MLDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is forThis machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.