Azure ML has a top-level component which is the Workspace. The workspace contains all the components of the Azure Machine Learning space.
The workspace is associated with
- Azure subscription
- Azure Key Vault
- Azure Application Insights
It is associated with the following assets
- Datasets
- Experiments
- Pipelines
- Models
- EndPoints
The workspace manages the following
- Datastores
- Compute
The workspace can be used for authoring
- Notebooks
- Automated ML
- Designer
You can implement via code
import azureml.core print(azureml.core.VERSION)
from azureml.core import Workspace from azureml.core.authentication import InteractiveLoginAuthentication sid = <your-subscription-id> forced_interactive_auth = InteractiveLoginAuthentication(tenant_id=<your-tenant-id>) ws = Workspace.create(name='azureml_workspace', subscription_id= sid, resource_group='rgazureml', create_resource_group = True, location='centralus' )
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