new gifs + edit step

Author: nibaccam

articles/machine-learning/how-to-use-automated-ml-for-ml-models.md

@@ -89,7 +89,9 @@ Otherwise, you'll see a list of your recent automated  ML experiments, including
 
 1. Select a target column; this is the column that you would like to do predictions on.
 
-1. Select a compute for the data profiling and training job. A list of your existing computes is available in the dropdown. To create a new compute, follow the instructions in step 7.
+1. Select a compute type for the data profiling and training job. You can select a [compute cluster](concept-compute-target.md#azure-machine-learning-compute-managed) or [compute instance](concept-compute-instance.md). 
+    
+1. Select a compute from the dropdown list of your existing computes.  To create a new compute, follow the instructions in step 8.
 
 1. Select **Create a new compute** to configure your compute context for this experiment.
 

articles/machine-learning/media/how-to-use-automated-ml-for-ml-models/explore-models.gif

@@ -107,9 +107,11 @@ After you load and configure your data, set up your remote compute target and se
 
     1. Select **cnt** as the target column, what you want to predict. This column indicates the number of total bike share rentals.
 
-    1. Select **Create a new compute** and configure your compute target. Automated ML only supports Azure Machine Learning compute. 
+    1. Select **compute cluster** as your compute type. 
 
-        1. Populate the **Virtual Machine** form to set up your compute.
+    1. Select **+New** to configure your compute target. Automated ML only supports Azure Machine Learning compute. 
+
+        1. Populate the **Select virtual machine** form to set up your compute.
 
             Field | Description | Value for tutorial
             ----|---|---
@@ -123,7 +125,7 @@ After you load and configure your data, set up your remote compute target and se
             ----|---|---
             Compute name |	A unique name that identifies your compute context. | bike-compute
             Min / Max nodes| To profile data, you must specify 1 or more nodes.|Min nodes: 1<br>Max nodes: 6
-            Idle seconds before scale down | Idle time before  the cluster is automatically scaled down to the minimum node count.|120 (default)
+            Idle seconds before scale down | Idle time before  the cluster is automatically scaled down to the minimum node count.|1800 (default)
             Advanced settings | Settings to configure and authorize a virtual network for your experiment.| None 
 
         1. Select **Create** to get the compute target. 

articles/machine-learning/media/tutorial-automated-ml-forecast/explore-models.gif

@@ -124,8 +124,10 @@ After you load and configure your data, you can set up your experiment. This set
 
     1. Select **y** as the target column, what you want to predict. This column indicates whether the client subscribed to a term deposit or not.
 
-    1. Select **+Create a new compute** and configure your compute target. A compute target is a local or cloud-based resource environment used to run your training script or host your service deployment. For this experiment, we use a cloud-based compute. 
-        1. Populate the **Virtual Machine** form to set up your compute.
+    1. Select **compute cluster** as your compute type. 
+    
+    1.  **+New** to configure your compute target. A compute target is a local or cloud-based resource environment used to run your training script or host your service deployment. For this experiment, we use a cloud-based compute. 
+        1. Populate the **Select virtual machine** form to set up your compute.
 
             Field | Description | Value for tutorial
             ----|---|---