Acrolinx

Author: v-dirichards

articles/machine-learning/how-to-share-models-pipelines-across-workspaces-with-registries.md

@@ -297,7 +297,7 @@ ml_client_registry.components.create_or_update(train_model)
 
 Note down the `name` and `version` of the component from the output and pass them to the `ml_client_registry.component.get()` method to fetch the component from registry. 
 
-You can also use `ml_client_registry.component.list()` to list all components in the registry or browse all components in the Azure Machine Learning Studio UI. Make sure you navigate to the global UI and look for the Registries hub.
+You can also use `ml_client_registry.component.list()` to list all components in the registry or browse all components in the Azure Machine Learning studio UI. Make sure you navigate to the global UI and look for the Registries hub.
 
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@@ -522,7 +522,7 @@ Note down the `name` and `version` of the model from the output of the `az ml mo
 az ml model show --name <model_name> --version <model_version> --registry-name <registry-name>
 ```
 
-You can also use `az ml model list --registry-name <registry-name>` to list all models in the registry or browse all components in the Azure Machine Learning Studio UI. Make sure you navigate to the global UI and look for the Registries hub.
+You can also use `az ml model list --registry-name <registry-name>` to list all models in the registry or browse all components in the Azure Machine Learning studio UI. Make sure you navigate to the global UI and look for the Registries hub.
 
 # [Python SDK](#tab/python)
 
@@ -579,7 +579,7 @@ Note down the `name` and `version` of the model from the output and use them wit
 mlflow_model_from_registry = ml_client_registry.models.get(name="nyc-taxi-model", version=str(1))
 print(mlflow_model_from_registry)
 ```
-You can also use `ml_client_registry.models.list()` to list all models in the registry or browse all components in the Azure Machine Learning Studio UI. Make sure you navigate to the global UI and look for the Registries hub.
+You can also use `ml_client_registry.models.list()` to list all models in the registry or browse all components in the Azure Machine Learning studio UI. Make sure you navigate to the global UI and look for the Registries hub.
 
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