Getting Started with Creating and Sharing Azure Machine Learning Studio Workspace

In this blog we shall learn how to create and share Microsoft Azure machine learning studio workspace using Microsoft Azure portal.


In this blog we shall learn how to create and share Microsoft Azure machine learning studio workspace using Microsoft Azure portal.

For novice Cloud developers, and all other IT professionals associated with Cloud Big Data analytics especially with Microsoft Azure, this blog will help to get started with Microsoft Azure Machine learning.


  • Microsoft Azure Subscription. (You can have your free trial subscription)
  • Zeal to Learn


To enable computer understand from data and repetitive functional flow experiences along with making it to respond with no coding involved is, Machine learning.It helps to build powerful Artificial Intelligence (AI) applications which enables increase in speed and productivity helping organization to accomplish profitable targets.

With continuing the same capabilities and feature, Machine Learning is now knowns as Machine Learning Studio. A powerful managed service enabling users to seamlessly build and share predictive analytics solutions.

Studio is a simple browser-based, collaborative, and serverless, with drag and drop environment, wherein experimentation can be achieved with zero coding. Also, studio makes deployments of services seamless with fewer clicks.

To use Azure Machine Learning Studio, we need to have a Machine Learning workspace. This workspace contains the tools you need to create, manage, and publish experiments.

Getting Started

Create Azure Machine Learning workspace

Open Microsoft Azure Portal in browser.

Click on New.

Enter ‘Machine Learning Workspace‘ in search box. (You can directly enter Machine Learning Studio Workspace)

Click on ‘Machine Learning Studio Workspace

This will open a blade with service details providing related important links for documentation, overview etc.

Click on ‘Create

Enter below mandatory details for creating Workspace,

  • Workspace name: Enter name for your Workspace
  • Subscription: Microsoft Azure Subscription.
  • Resource group: Being part of Azure services, it needs to be deployed under Resource group. You can create new or select from existing resource group.
  • Location: Location where service will be deployed.
  • Storage: If you are creating workspace for the first time, it will allow only to create a new storage account. This will create an Azure storage account with standard performance and LRS replication. If you are trying to select from existing storage account, it will get filtered with selected Location. Also, Blob storage and premium tier storage are not supported. We need to only go with existing general purpose storage account
  • Workspace Pricing Tier: Workspace will be charged according to Standard pricing tier.
  • Web service plan: This plan will be used by web services deployed from this workspace.

  • Web service plan pricing tier: Select from different pricing tier available for Machine leaning studio web services.

For this blog we have entered details as follows,

  • Workspace name: Given name as learn-machinelearning
  • Subscription: Microsoft Azure Subscription – Free Trial
  • Resource group: Created new resource group, learnmachinelearning.
  • Location: South Central US, default location selected.
  • Storage: Creating new Storage account with name, learnmachinelearnstorage.
  • Workspace Pricing Tier: Standard.
  • Web service plan: Given Name as, learn-machinelearningplan
  • Web service plan pricing tier: Selected DevTestStandardtier, as shown in above image.

Navigate to Resource Group.

Click on newly created resource group.

Azure storage account, Web service plan and Studio Workspace are deployed and listed under Resource group section.

Click on Machine Learning Studio workspace => Navigate to Overview section

Now launch Machine Learning Studio by clicking on Link being provided in Additional Links under overview section.

Machine Learning Studio will get launched in new tab in browser or new browser as your machine settings.

Click on Sign In => Enter same credentials as of Microsoft Azure account.

After successful login, select your workspace in the upper-right-hand corner.

Click on Experiments.

We are done with creating Machine learning workspace for managing our experiments.

Sharing Azure Machine Learning workspace

In Machine Learning Studio =>Workspace

Click on Settings => Select USERS

Click ‘Invite More Users‘ from bottom are of page.

Refer below image.

This will open up window, asking to specify User’s email id we need to share this workspace with.

Enter one or more email addresses. The users need a valid Microsoft account or an organizational account (from Azure Active Directory).

We can add user as,

  • Users: A workspace user can list, clone and create experiments and datasets in the workspace.
  • Owner: An owner can add, remove and list users with access to the workspace, in addition to what a user can do.

For this blog, we shall add user as Owner.

Click on OK checkmark button at bottom right corner, highlighted in above image.

User gets notified via email with instructions on how to sign in to the shared workspace .and will need to sign-in using that account to get workspace access

Newly added User details like Name, Email ID, Role along with Status as Invited will be listed under USERS tab.

Once invited user logins with his/her email id, this status updates to Active.


In this blog, CRM developer India team explained how easy it is to get started with creating Microsoft Azure Machine Learning Studio workspace and sharing the same with co-members or team for productive experiments.

Would recommend to use above learning and try this super cool studio.

Thank You!

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Vijay is a compulsive blogger who likes to educate like-minded people on various new technologies and trends. He works with Aegis SoftTech as a software developer and has been developing software for years. Stay Connected to him on Facebook and Google+.