The workspace is the central place where you can work with all resources and assets available to train and deploy ML models. To get access to an Azure Machine Learning workspace, you first need to create the Azure Machine Learning service in your Azure subscription.

Understand the Azure Machine Learning service

• Navigate to azure portal

• Sign in to get acces to an Azure Subscription
  

• Create resource group with in your subscription

• Create an Azure Machine Learning service to create a workspace. When a workspace is provisioned, Azure will automatically create other Azure resources within the same resource group to support the workspace:

• Azure Storage Account: To store files and notebooks used in the workspace, and to store metadata of jobs and models.
• Azure Key Vault: To securely manage secrets such as authentication keys and credentials used by the workspace.
• Application Insights: To monitor predictive services in the workspace.
• Azure Container Registry: Created when needed to store images for Azure Machine Learning environments.