Gain insights into Azure basics, build ML/deep learning pipelines, manage deployments, and analyze models ethically with responsible AI, ensuring fairness and bias mitigation.

“Build, Deploy MachineDeep Learning Models using Azure CLI”.png

azure.tar.gz

UserName

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ResourceGroup

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Compute

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ComputeCreate-yml

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Storage Account Creation

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Storage Blob Upload

Storage Blob Download

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JobCreate

Job-run-SPA

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VMList

Model-Create-SPA

Component-Create-SPA

endpoint-Create-SPA

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endpoint-uai-create-SPA

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endpoint-local-Create-SPA

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VM-Create-SPA

PrivateWorkspaceCreation-copy

endpoint-Create-Local-SPA

deployment-batch-invoke

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In this course, you will start your journey by gaining a comprehensive understanding of the basics of Azure, including creating and managing Azure resources, and setting up the Azure CLI environment. 

Next, you will learn how to build Azure Machine Learning pipelines from scratch. Then, you’ll delve into deep learning and distributed deep learning pipelines. You’ll learn how to manage the deployment and scheduling of these models. You’ll also cover the complete model management strategies. Finally, the course will cover model analysis using responsible AI, teaching how to identify and mitigate potential biases in models and ensuring that models are ethical and fair. You’ll also learn how to analyze the models and identify potential areas for improvement.

By the end of this course, you’ll have a comprehensive understanding of Azure Machine Learning, including how to build complex pipelines, deploy models using online/batch methods, and manage and analyze models using tools like MLflow and responsible AI.

Designing Machine/Deep Learning Models Using Azure CLI

The Azure CLI update is available for Windows, Linux, and macOS operating systems. We can also run the CLI using the Docker environment or directly from Azure Cloud Shell (the versions might be different). We have already explained how to use Azure Cloud Shell in the previous lessons.

# Installation on Windows

To get the installer for Windows, [visit this link](https://aka.ms/installazurecliwindows).




 


After the installation, run the below command from the command prompt.

If the command outputs show the help content, we can confirm that the installation worked. The command below will print the Azure CLI version on the running machine.





If the version is `2.14.0`, then only a machine learning extension is available. Use the below command to upgrade the Azure CLI version.



Now, add the `ml extension` for building ML applications. 
Before installing, remove any previous extensions of Azure Machine Learning. Let's make sure that we have the latest version of the Azure Machine Learning extension available.

Let’s go ahead and install Azure CLI on Windows, Linux, and macOS systems.

Setup and Installation

Introduction

Getting Started

Creating Azure Resources

Building Azure ML Pipeline

Building a diabetes model pipeline

Service Deployment

Creating a Deep Learning Pipeline

Detect Posture Project

Conclusion

Appendix

Sentiment Analysis Using Natural Language Processing

Setup and Installation

Installation on Windows