Azure Machine Learning Engineering


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Azure Machine Learning Engineering


Azure Machine Learning Engineering

Author: Sina Fakhraee

language: en

Publisher: Packt Publishing Ltd

Release Date: 2023-01-20


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Fully build and productionize end-to-end machine learning solutions using Azure Machine Learning Service Key FeaturesAutomate complete machine learning solutions using Microsoft AzureUnderstand how to productionize machine learning modelsGet to grips with monitoring, MLOps, deep learning, distributed training, and reinforcement learningBook Description Data scientists working on productionizing machine learning (ML) workloads face a breadth of challenges at every step owing to the countless factors involved in getting ML models deployed and running. This book offers solutions to common issues, detailed explanations of essential concepts, and step-by-step instructions to productionize ML workloads using the Azure Machine Learning service. You'll see how data scientists and ML engineers working with Microsoft Azure can train and deploy ML models at scale by putting their knowledge to work with this practical guide. Throughout the book, you'll learn how to train, register, and productionize ML models by making use of the power of the Azure Machine Learning service. You'll get to grips with scoring models in real time and batch, explaining models to earn business trust, mitigating model bias, and developing solutions using an MLOps framework. By the end of this Azure Machine Learning book, you'll be ready to build and deploy end-to-end ML solutions into a production system using the Azure Machine Learning service for real-time scenarios. What you will learnTrain ML models in the Azure Machine Learning serviceBuild end-to-end ML pipelinesHost ML models on real-time scoring endpointsMitigate bias in ML modelsGet the hang of using an MLOps framework to productionize modelsSimplify ML model explainability using the Azure Machine Learning service and Azure InterpretWho this book is for Machine learning engineers and data scientists who want to move to ML engineering roles will find this AMLS book useful. Familiarity with the Azure ecosystem will assist with understanding the concepts covered.

Microsoft Azure Machine Learning


Microsoft Azure Machine Learning

Author: Sumit Mund

language: en

Publisher:

Release Date: 2015-06-16


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The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

Microsoft Azure Essentials Azure Machine Learning


Microsoft Azure Essentials Azure Machine Learning

Author: Jeff Barnes

language: en

Publisher: Microsoft Press

Release Date: 2015-04-25


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Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.