Typo fix

Author: PeterCLu

articles/machine-learning/how-to-debug-pipelines.md

@@ -133,8 +133,8 @@ For pipelines created in the designer, you can find the **log files** on either
 When you submit a pipeline run and stay in the authoring page, you can find the log files generated for each module.
 
 1. Select any module in the authoring canvas.
-1. In the right pane of the module, go to the  **Outputs+logs** tab.
-1. Select the log file `70_driver_log.txt`
+1. In the right pane of the module, go to the  **Outputs + logs** tab.
+1. Select the log file `70_driver_log.txt`.
 
     ![Authoring page module logs](./media/how-to-debug-pipelines/pipelinerun-05.png)
 
@@ -145,8 +145,8 @@ You can also find the log files of specific runs in the pipeline run detail page
 1. Select a pipeline run created in the designer.
     ![Pipeline run page](./media/how-to-debug-pipelines/pipelinerun-04.png)
 1. Select any module in the preview pane.
-1. In the right pane of the module, go to the  **Outputs+logs** tab.
-1. Select the log file `70_driver_log.txt`
+1. In the right pane of the module, go to the  **Outputs + logs** tab.
+1. Select the log file `70_driver_log.txt`.
 
 ## Debug and troubleshoot in Application Insights
 For more information on using the OpenCensus Python library in this manner, see this guide: [Debug and troubleshoot machine learning pipelines in Application Insights](how-to-debug-pipelines-application-insights.md)

articles/machine-learning/samples-designer.md

@@ -9,7 +9,7 @@ ms.topic: sample
 
 author: peterclu
 ms.author: peterlu
-ms.date: 03/10/2020
+ms.date: 03/29/2020
 ---
 # Designer sample pipelines
 
@@ -25,6 +25,8 @@ Use the built-in examples in Azure Machine Learning designer to quickly get star
 
 The designer saves a copy of the sample pipelines to your studio workspace. You can edit the pipeline to adapt it to your needs and save it as your own. Use them as a starting point to jumpstart your projects.
 
+### Open a sample pipeline
+
 1. Sign in to <a href="https://ml.azure.com?tabs=jre" target="_blank">ml.azure.com</a>, and select the workspace you want to work with.
 
 1. Select **Designer**.
@@ -33,6 +35,31 @@ The designer saves a copy of the sample pipelines to your studio workspace. You
 
     Select **Show more samples** for a complete list of samples.
 
+### Submit a pipeline run
+
+To run a pipeline, you first have to set default compute target to run the pipeline on.
+
+1. In the **Settings** pane to the right of the canvas, select **Select compute target**.
+
+1. In the dialog that appears, select an existing compute target or create a new one. Select **Save**.
+
+1. Select **Submit** at the top of the canvas to submit a pipeline run.
+
+Depending on the sample pipeline and compute settings, runs may take some time to complete. The default compute settings have a minimum node size of 0, which means that the designer must allocate resources after being idle. Repeated pipeline runs will take less time since the compute resources are already allocated. Additionally, the designer uses cached results for each module to further improve efficiency.
+
+
+### Review the results
+
+After the pipeline finishes running, you can review the pipeline and view the output for each module to learn more.
+
+Use the following steps to view module outputs:
+
+1. Select a module in the canvas.
+
+1. In the module details pane to the right of the canvas, select **Outputs + logs**. Select the graph icon ![visualize icon](./media/tutorial-designer-automobile-price-train-score/visualize-icon.png) to see the results of each module. 
+
+Use the samples as starting points for some of the most common machine learning scenarios.
+
 ## Regression samples
 
 Learn more about the built-in regression samples.