fix blocking changes

Author: sdgilley

articles/machine-learning/how-to-create-attach-compute-cluster.md

@@ -126,7 +126,7 @@ Create a single- or multi- node compute cluster for your training, batch inferen
 1. Under __Manage__, select __Compute__.
 1. If you have no compute resources, select  **Create** in the middle of the page.
 
-    :::image type="content" source="media/how-to-create-attach-studio/create-compute-target.png" alt-text="Create compute target":::
+    :::image type="content" source="media/how-to-create-attach-studio/create-compute-target.png" alt-text="Screenshot that shows creating a compute target":::
 
 1. If you see a list of compute resources, select **+New** above the list.
 
@@ -147,7 +147,7 @@ Create a single- or multi- node compute cluster for your training, batch inferen
 
     |Field  |Description  |
     |---------|---------|
-    |Compute name     |  <li>Name is required and must be between 3 to 24 characters long.</li><li>Valid characters are upper and lower case letters, digits, and the  **-** character.</li><li>Name must start with a letter</li><li>Name needs to be unique across all existing computes within an Azure region. You'll see an alert if the name you choose isn't unique</li><li>If **-**  character is used, then it needs to be followed by at least one letter later in the name</li>     |
+    |Compute name     | <ul> <li>Name is required and must be between 3 to 24 characters long.</li><li>Valid characters are upper and lower case letters, digits, and the  **-** character.</li><li>Name must start with a letter</li><li>Name needs to be unique across all existing computes within an Azure region. You'll see an alert if the name you choose isn't unique</li><li>If **-**  character is used, then it needs to be followed by at least one letter later in the name</li> </ul>    |
     |Minimum number of nodes | Minimum number of nodes that you want to provision. If you want a dedicated number of nodes, set that count here. Save money by setting the minimum to 0, so you won't pay for any nodes when the cluster is idle. |
     |Maximum number of nodes | Maximum number of nodes that you want to provision. The compute will autoscale to a maximum of this node count when a job is submitted. |
     | Idle seconds before scale down | Idle time before scaling the cluster down to the minimum node count. |

articles/machine-learning/how-to-create-attach-compute-studio.md

@@ -1,7 +1,7 @@
 ---
 title: Manage training & deploy computes (studio)
 titleSuffix: Azure Machine Learning
-description: Use studio to manage training and deployment compute resources (compute targets) for machine learning
+description: Use studio to manage training and deployment compute resources (compute targets) for machine learning.
 services: machine-learning
 author: sdgilley
 ms.author: sgilley
@@ -23,7 +23,7 @@ In this article, learn how to manage the compute resources you use for model tra
 
 ## What's a compute target?
 
-With Azure Machine Learning, you can train your model on a variety of resources or environments, collectively referred to as _compute targets_). A compute target can be a local machine or a cloud resource, such as an Azure Machine Learning Compute, Azure HDInsight, or a remote virtual machine.  You can also create compute targets for model deployment as described in ["Where and how to deploy your models"](how-to-deploy-and-where.md).
+With Azure Machine Learning, you can train your model on a variety of resources or environments, collectively referred to as _compute targets_). A compute target can be a local machine or a cloud resource, such as an Azure Machine Learning Compute, Azure HDInsight, or a remote virtual machine. 
 
 ## View compute targets
 
@@ -44,7 +44,7 @@ You can create compute instances and compute clusters in your workspace, using t
 * [Compute instance](how-to-create-manage-compute-instance.md)
 * [Compute cluster](how-to-create-attach-compute-cluster.md)
 
-In additions, you can use the [VS Code extension](how-to-manage-resources-vscode.md#compute-clusters) to create compute instances and compute clusters in your workspace.
+In addition, you can use the [VS Code extension](how-to-manage-resources-vscode.md#compute-clusters) to create compute instances and compute clusters in your workspace.
 
 ## Kubernetes cluster
 

includes/machine-learning-ssh-access.md

@@ -16,10 +16,10 @@ After you create a compute with SSH access enabled, use these steps for access.
 
     * For a **compute instance**, select **Connect** at the top of the **Details** section.
 
-        :::image type="content" source="../articles/machine-learning/media/how-to-create-attach-studio/details.png" alt-text="Screenshot: Connect tool at the top of the Details page.":::
+        :::image type="content" source="../articles/machine-learning/media/how-to-create-attach-studio/details.png" alt-text="Screenshot that shows connect tool at the top of the Details page.":::
 
     * For a **compute cluster**, select **Nodes** at the top, then select the **Connection string** in the table for your node.
-        :::image type="content" source="../articles/machine-learning/media/how-to-create-attach-studio/compute-nodes.png" alt-text="Screenshot: Connection string for a node in a compute cluster.":::
+        :::image type="content" source="../articles/machine-learning/media/how-to-create-attach-studio/compute-nodes.png" alt-text="Screenshot that shows connection string for a node in a compute cluster.":::
 
 1. Copy the connection string.
 1. For Windows, open PowerShell or a command prompt: