Learn Machine Learning on Microsoft Azure by Doing:How to create your first Azure ML workspace?

Looking to get started with Machine Learning on Microsoft Azure? Well, you’ve come to the right place! In this guide, we will cover the first step in order to build your first Data science project in Azure which is to setup an Azure Machine Learning workspace .Let’s started!

Introduction

What is Azure Machine Learning workspace?

• The workspace is the top-level resource for Azure Machine Learning.
• providing a centralized place to work with all the artifacts you create when you use Azure Machine Learning.
• The workspace keeps a history of all training runs, including logs, metrics, output, and a snapshot of your scripts.

Task Steps

Step 1: Log In to the Azure Portal

• I’m currently on the Azure portal in the URL https://portal.azure.com/
• This is the home page for any operation in Azure and here we’ll configure the machine learning workspace and launch the studio which is a web interface to manage the workspace .

Azure Portal

Step 2: Create a Ressource group

• This is a best practice because after we’re done with Azure ML ,we can easily delete everything and not get overcharged by deleting the ressource group.
• Click on Ressource groups and later on Create, and there we’re.

Ressouce group configuration

• Select the subscription( pay as you go OR free subscription)
• Give your ressouce group a name (in my case pluralsight-azure-ml).
• Click on Review +Create and then on Create to create a ressouce group.

• Our ressouce group is created !

• Click on the ressource group and from here click on Create,here we’re.

Step 3: Choose Machine Learning in order to create an ML workspace

• On the search bar type machine learning and then click on Create .

• Click on Create ,and here we’re on the creation page.
• Name the workspce however we prefer (in my case pluralsigt-Azure-ml).
• it auto created a text for us for the other accounts.

• Here we are,the deployment is complete!

• Click on Go to Ressource
• Here we can find all the informations about the ressource.

• you can click on Launch studio in the buttom in order to launch a machine learning studio .
• This is a machine learning studio with all the different options in the left panel like:checking the endpoints deployed,the model pipelines or cheching the datasets.

And here we’re !

You’re all done! Congratulations!

That’s all I have for today folks. Thank you for reading and/or following along! I hope this project was helpful and worth your while. Stay tuned for my next project.

Let’s connect on LinkedIn! 👉 https://www.linkedin.com/in/meriem-terki-1295a1222/