Azure Machine Learning Engineering: Deploy, fine-tune, and optimize ML models using Microsoft Azure

Author:   Sina Fakhraee ,  Balamurugan Balakreshnan ,  Megan Masanz
Publisher:   Packt Publishing Limited
ISBN:  

9781803239309


Pages:   362
Publication Date:   13 January 2023
Format:   Paperback
Availability:   Available To Order   Availability explained
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Azure Machine Learning Engineering: Deploy, fine-tune, and optimize ML models using Microsoft Azure


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Author:   Sina Fakhraee ,  Balamurugan Balakreshnan ,  Megan Masanz
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
ISBN:  

9781803239309


ISBN 10:   1803239301
Pages:   362
Publication Date:   13 January 2023
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Table of Contents Introducing Azure Machine Learning Working with Data in AMLS Training Machine Learning Models in AMLS Tuning Your Models with AMLS Azure Automated Machine Learning Deploying ML Models for Real-Time Inferencing Deploying ML Models for Batch Scoring Responsible AI Productionizing Your Workload with MLOps Using Deep Learning in Azure Machine Learning Using Distributed Training in AMLS

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Author Information

Sina Fakhraee, Ph.D., is currently working at Microsoft as an enterprise data scientist and senior cloud solution architect. He has helped customers to successfully migrate to Azure by providing best practices around data and AI architectural design and by helping them implement AI/ML solutions on Azure. Prior to working at Microsoft, Sina worked at Ford Motor Company as a product owner for Ford's AI/ML platform. Sina holds a Ph.D. degree in computer science and engineering from Wayne State University and prior to joining the industry, he taught various undergrad and grad computer science courses part time. Balamurugan Balakreshnan is a principal cloud solution architect at Microsoft Data/AI Architect and Data Science. He has provided leadership on digital transformations with AI and cloud-based digital solutions. He has also provided leadership in terms of ML, the IoT, big data, and advanced analytical solutions. Megan Masanz is a principal cloud solution architect at Microsoft focused on data, AI, and data science, passionately enabling organizations to address business challenges through the establishment of strategies and road maps for the planning, design, and deployment of Azure Cloud-based solutions. Megan is adept at paving the path to data science via computer science given her master's in computer science with a focus on data science.

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