Create an Azure Machine Learning workspace

In this article, we will explore how to create an Azure Machine Learning workspace. Creating a workspace is the first step towards leveraging Azure’s powerful data science and machine learning capabilities. By creating a workspace, you can easily manage and track your experiments, models, and deployments in a centralized and collaborative environment.

Prerequisites

To follow along with this tutorial, you will need:

1. An Azure subscription. If you don’t have one, you can sign up for a free account here.
2. Access to the Azure portal. You can access the portal here.

Creating an Azure Machine Learning Workspace

To create an Azure Machine Learning workspace, follow these steps:

1. Sign in to the Azure portal.
2. Click on the Create a resource button (+) on the top left-hand side of the portal.
3. In the search bar, type “Machine Learning” and select Machine Learning from the search results.
4. Click on the Create button to begin configuring your workspace.

Basics

1. In the Basics tab of the creation wizard, fill in the following details:
   • Subscription: Select the Azure subscription you want to use.
   • Resource group: Choose an existing resource group or create a new one.
   • Workspace name: Enter a unique name for your workspace.
   • Region: Select the region closest to your location.
   • Storage account: Choose an existing storage account or create a new one.

   
2. Click on the Next: Networking button to proceed.

Networking

1. In the Networking tab, you can configure the network settings for your workspace.




2. Click on the Next: Advanced button to proceed.

Advanced

1. In the Advanced tab, you have the option to configure advanced settings like virtual networks, private endpoints, etc. For this tutorial, we will leave the default settings.




2. Click on the Next: Tags button to proceed.

Tags

1. In the Tags tab, you can add tags to your workspace for easy organization and management.




2. Click on the Next: Review + create button to proceed.

Review + create

1. In the Review + create tab, review the details of your workspace configuration.




2. Once you have reviewed the details, click on the Create button to create your workspace.

Workspace creation

1. Azure will now begin creating your Machine Learning workspace. This process may take a few minutes.




2. Once the deployment is complete, you will see a notification in the portal.

Congratulations! You have successfully created an Azure Machine Learning workspace. You can now start leveraging the power of Azure’s data science and machine learning capabilities.

Summary

In this tutorial, we explored how to create an Azure Machine Learning workspace. By creating a workspace, you can easily manage and track your experiments, models, and deployments. We went through each step of the workspace creation process, including configuring the basics, networking, advanced settings, and review. Now you are ready to start your data science journey on Azure!