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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