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Optimizing Microsoft Azure AI Solutions

Microsoft's cloud-based platform Azure provides multiple AI services such as AzureML Compute Cluster, Azure HDInsight, Azure Databricks, Azure DevOps. In this course you will learn how to design, deploy, and optimize applications built with Microsoft AI Solutions.

Advanced
1h 27m
(18)

Created by Ranjan Relan

Last Updated Sep 14, 2020

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  • Course

Optimizing Microsoft Azure AI Solutions

Microsoft's cloud-based platform Azure provides multiple AI services such as AzureML Compute Cluster, Azure HDInsight, Azure Databricks, Azure DevOps. In this course you will learn how to design, deploy, and optimize applications built with Microsoft AI Solutions.

Advanced
1h 27m
(18)

Created by Ranjan Relan

Last Updated Sep 14, 2020

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What you'll learn

Cloud-based platform Microsoft Azure has multiple AI services which could be used to train your model for big data sets as well as to deploy your model as a web service. In this course, Optimizing Microsoft Azure AI Solutions, you will learn the foundational knowledge of how to train your machine learning models using Azure's services such AzureML Compute Cluster, Azure HDInsight, Azure Databricks, and Azure Data Science Virtual Machine. Next, you will discover how to optimize your storage by using Azure Premium blob storage service and data formats such as Pickle and Parquet. Finally, you will explore how to scale your machine learning models and manage end-to-end machine learning life cycle using the principle of MLOps. When you’re finished with this course, you will have the skills and knowledge of Mircosoft Azure's core AI services needed to design, deploy, and optimize your model.

Optimizing Microsoft Azure AI Solutions
Advanced
1h 27m
(18)
Table of contents

About the author
Ranjan Relan - Pluralsight course - Optimizing Microsoft Azure AI Solutions
Ranjan Relan
7 courses 4.3 author rating 228 ratings

Ranjan Relan is a Data and Tech Strategy Consultant with 11+ years of experience in the field of Machine Learning, Big Data, Cloud Computing and Data warehousing.

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