more focus on why

sdgilley · sdgilley · commit bcdf483a4f1e · 2019-05-17T16:01:39.000-05:00
diff --git a/articles/machine-learning/service/quickstart-run-cloud-notebook.md b/articles/machine-learning/service/quickstart-run-cloud-notebook.md
@@ -17,7 +17,7 @@ ms.custom: seodec18
 
 No install required.  Get started with Azure Machine Learning service using a managed notebook server in the cloud. If you want to instead install the SDK into your own Python environment, see [Quickstart: Use your own notebook server to get started with Azure Machine Learning](quickstart-run-local-notebook.md).
 
-This quickstart shows how to create a [notebook VM (Preview)](how-to-configure-environment.md#notebookvm), a secure, cloud-based Azure workstation that provides a Jupyter notebook server, JupyterLab, and a fully prepared ML environment. You then run a Python notebook on this VM to logs values into the [Azure Machine Learning service workspace](concept-azure-machine-learning-architecture.md). The workspace is the foundational block in the cloud that you use to experiment, train, and deploy machine learning models with Machine Learning.
+This quickstart shows how you can use the [Azure Machine Learning service workspace](concept-azure-machine-learning-architecture.md) to keep track of your machine learning experiments.  You will create a [notebook VM (Preview)](how-to-configure-environment.md#notebookvm), a secure, cloud-based Azure workstation that provides a Jupyter notebook server, JupyterLab, and a fully prepared ML environment. You then run a Python notebook on this VM that log values into the workspace.
 
 In this quickstart, you take the following actions:
 
diff --git a/articles/machine-learning/service/quickstart-run-local-notebook.md b/articles/machine-learning/service/quickstart-run-local-notebook.md
@@ -17,7 +17,7 @@ ms.custom: seodec18
 
 Use your own Python environment and Jupyter Notebook Server to get started with Azure Machine Learning service.  For a quickstart with no SDK installation, see [Quickstart: Use a cloud-based notebook server to get started with Azure Machine Learning](quickstart-run-cloud-notebook.md).
 
-In this quickstart, you run code that logs values into the [Azure Machine Learning service workspace](concept-azure-machine-learning-architecture.md). The workspace is the foundational block in the cloud that you use to experiment, train, and deploy machine learning models with Machine Learning.  
+This quickstart shows how you can use the [Azure Machine Learning service workspace](concept-azure-machine-learning-architecture.md) to keep track of your machine learning experiments. You will run Python code that log values into the workspace.
 
 View a video version of this quickstart:
 
