Merge pull request #92117 from cartacioS/patch-19

Updating ADB AutoML info

Author: TedA-M

articles/machine-learning/service/how-to-configure-environment.md

@@ -300,7 +300,7 @@ Use these settings:
 | Setting |Applies to| Value |
 |----|---|---|
 | Cluster name |always| yourclustername |
-| Databricks Runtime |always| Any non-ML runtime (non-ML 4.x, 5.x) |
+| Databricks Runtime |always|Non-ML Runtime 6.0 (scala 2.11, spark 2.4.3) |
 | Python version |always| 3 |
 | Workers |always| 2 or higher |
 | Worker node VM types <br>(determines max # of concurrent iterations) |Automated ML<br>only| Memory optimized VM preferred |
@@ -345,13 +345,17 @@ SDK for Databricks **_without_** automated machine learning
 ![Azure Machine Learning SDK for Databricks](./media/how-to-configure-environment/amlsdk-withoutautoml.jpg)
 
 SDK for Databricks **WITH** automated machine learning
-![SDK with automated machine learning installed on Databricks](./media/how-to-configure-environment/automlonadb.jpg)
+![SDK with automated machine learning installed on Databricks](./media/how-to-configure-environment/automlonadb.png)
 
 ### Start exploring
 
 Try it out:
 + While many sample notebooks are available, **only [these sample notebooks](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/azure-databricks) work with Azure Databricks.**
 
++ Import these samples directly from your workspace. See below:
+![Select Import](media/how-to-configure-environment/azure-db-screenshot.png)
+![Import Panel](media/how-to-configure-environment/azure-db-import.png)
+
 + Learn how to [create a pipeline with Databricks as the training compute](how-to-create-your-first-pipeline.md).
 
 ## <a id="workspace"></a>Create a workspace configuration file