Apply suggestions from code review

Co-authored-by: Mope Akande <[email protected]>

Author: shohei1029

articles/machine-learning/how-to-troubleshoot-online-endpoints.md

@@ -160,13 +160,13 @@ ml_client.online_deployments.get_logs(
 
 # [Studio](#tab/studio)
 
-To see log output from container, use the **Endpoints** in the studio:
+To see log output from a container, use the **Endpoints** in the studio:
 
 1. In the left navigation bar, select Endpoints.
-1. (Optional) Create a Filter on Compute type to show only Managed compute types.
-1. Select an endpoint name to view the endpoint detail page.
-1. Select the **Deployment logs** tab in the endpoint's detail page.
-1. User the dropdown to select the deployment you want to see the log.
+1. (Optional) Create a filter on compute type to show only managed compute types.
+1. Select an endpoint's name to view the endpoint's details page.
+1. Select the **Deployment logs** tab in the endpoint's details page.
+1. Use the dropdown to select the deployment whose log you want to see.
 
 :::image type="content" source="media/how-to-troubleshoot-online-endpoints/deployment-logs.png" lightbox="media/how-to-troubleshoot-online-endpoints/deployment-logs.png" alt-text="A screenshot of observing deployment logs in the studio.":::
 
@@ -314,9 +314,9 @@ Use the **Endpoints** in the studio:
 
 1. In the left navigation bar, select **Endpoints**.
 1. (Optional) Create a filter on compute type to show only managed compute types.
-1. Select an endpoint name to view the endpoint detail page.
-1. Select the **Deployment logs** tab in the endpoint's detail page.
-1. User the dropdown to select the deployment you want to see the log.
+1. Select an endpoint name to view the endpoint's details page.
+1. Select the **Deployment logs** tab in the endpoint's details page.
+1. Use the dropdown to select the deployment whose log you want to see.
 
 ---
 
@@ -370,7 +370,7 @@ For example, if image is `testacr.azurecr.io/azureml/azureml_92a029f831ce58d2ed0
 
 #### Unable to download user model
 
-It is possible that the user model can't be found. Check [container logs](#get-container-logs) to get more details.
+It is possible that the user's model can't be found. Check [container logs](#get-container-logs) to get more details.
 
 Make sure the model is registered to the same workspace as the deployment. To show details for a model in a workspace: 
 
@@ -391,12 +391,12 @@ ml_client.models.get(name="<model-name>", version=<version>)
 See the **Models** page in the studio:
 
 1. In the left navigation bar, select Models.
-1. Select a model name to view the model detail page.
+1. Select a model's name to view the model's details page.
 
 ---
 
 > [!WARNING]
-> You must specify either version or label to get the model information.
+> You must specify either version or label to get the model's information.
 
 You can also check if the blobs are present in the workspace storage account.
 

articles/machine-learning/how-to-use-managed-online-endpoint-studio.md

@@ -109,11 +109,11 @@ To use the monitoring tab, you must select "**Enable Application Insight diagnos
 
 :::image type="content" source="media/how-to-create-managed-online-endpoint-studio/monitor-endpoint.png" lightbox="media/how-to-create-managed-online-endpoint-studio/monitor-endpoint.png" alt-text="A screenshot of monitoring endpoint-level metrics in the studio.":::
 
-For more information on how viewing other monitors and alerts, see [How to monitor managed online endpoints](how-to-monitor-online-endpoints.md).
+For more information on viewing other monitors and alerts, see [How to monitor managed online endpoints](how-to-monitor-online-endpoints.md).
 
 ### Deployment logs
 
-You can get logs from the containers that are running on the VM where the model is deployed. The amount of information depends on the provisioning status of the deployment. If the specified container is up and running you'll see its console output, otherwise you'll get a message to try again later.
+You can get logs from the containers that are running on the VM where the model is deployed. The amount of information you get depends on the provisioning status of the deployment. If the specified container is up and running, you'll see its console output; otherwise, you'll get a message to try again later.
 
 Use the **Deployment logs** tabs in the endpoint's details page to see log output from container.