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@@ -41,7 +41,7 @@ Azure Machine Learning distinguishes two types of URIs:
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Data type | Description | Examples
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`uri_file` | Refers to a specific **file** location | `https://<account_name>.blob.core.windows.net/<container_name>/<folder>/<file>`<br> `azureml://datastores/<datastore_name>/paths/<folder>/<file>` <br> `abfss://<file_system>@<account_name>.dfs.core.windows.net/<folder>/<file>`
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`uri_folder`| Refers to a specific **folder** location | `https://<account_name>.blob.core.windows.net/<container_name>/<folder>`<br> `azureml://datastores/<datastore_name>/paths/<folder>` <br> `abfss://<file_system>@<account_name>.dfs.core.windows.net/<folder>/`
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`uri_folder`| Refers to a specific **folder** location | `azureml://datastores/<datastore_name>/paths/<folder>` <br> `abfss://<file_system>@<account_name>.dfs.core.windows.net/<folder>/`
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URIs are mapped to the filesystem on the compute target, hence using URIs is like using files or folders in the command that consumes/produces them. URIs leverage **identity-based authentication** to connect to storage services with either your Azure Active Directory ID (default) or Managed Identity.
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