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Execute Large Scale End-to-End Machine Learning with Azure, 2nd Edition

Art Mitchell

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Published in Mastering Azure Machine Learning: Execute Large Scale End To End Machine Learning With Azure 2nd Edition

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Machine learning (ML) is a rapidly growing field that is transforming the way we live and work. Businesses of all sizes are using ML to improve their operations, make better decisions, and create new products and services. However, building and deploying ML models at scale can be a complex and challenging process.

Azure is a cloud computing platform that provides a wide range of services for building, deploying, and managing ML models. Azure's ML services are designed to make it easy for data scientists and developers to build and deploy ML models without having to worry about the underlying infrastructure.

Mastering Azure Machine Learning: Execute large-scale end-to-end machine learning with Azure, 2nd Edition

by Marcel Alsdorf

5 out of 5

Language	:	English
File size	:	22171 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	624 pages

Execute Large Scale End-to-End Machine Learning with Azure, 2nd Edition, provides a comprehensive guide to building, deploying, and managing ML models in a scalable and efficient manner using Microsoft Azure. This book is written for data scientists and developers who want to learn how to use Azure's ML services to build and deploy real-world ML solutions.

What's New in the 2nd Edition

The 2nd edition of Execute Large Scale End-to-End Machine Learning with Azure has been updated to include the latest changes to Azure's ML services. This includes new chapters on:

* Azure Machine Learning Pipelines * Azure Machine Learning Models * Azure Machine Learning Compute * Azure Machine Learning Datastores

In addition, the 2nd edition includes a number of new case studies and examples that show how to use Azure's ML services to solve real-world problems.

Who This Book Is For

* This book is written for data scientists and developers who want to learn how to use Azure's ML services to build and deploy real-world ML solutions. * No prior experience with Azure or ML is required. However, a basic understanding of programming and data science concepts is helpful.

What You Will Learn

* How to build, deploy, and manage ML models in a scalable and efficient manner using Microsoft Azure * How to use Azure's ML services to solve real-world problems * How to use Azure Machine Learning Pipelines to automate the ML lifecycle * How to use Azure Machine Learning Models to deploy ML models to production * How to use Azure Machine Learning Compute to provision and manage compute resources for ML training and inference * How to use Azure Machine Learning Datastores to store and manage data for ML training and inference

to Azure Machine Learning *

Azure Machine Learning Pipelines *

Azure Machine Learning Models *

Azure Machine Learning Compute *

Azure Machine Learning Datastores *

Case Studies *

Execute Large Scale End-to-End Machine Learning with Azure, 2nd Edition, is a comprehensive guide to building, deploying, and managing ML models in a scalable and efficient manner using Microsoft Azure. This book is a valuable resource for data scientists and developers who want to learn how to use Azure's ML services to build and deploy real-world ML solutions.

Mastering Azure Machine Learning: Execute large-scale end-to-end machine learning with Azure, 2nd Edition

by Marcel Alsdorf

5 out of 5