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databricks/automl_adb_readme.md

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+**PREVIEW capability** 
+
+Automated ML now supports Azure Databricks as a local compute to perform training (**public preview**). Azure Databricks is a managed Spark offering on Azure and customers already use it for advanced analytics. It provides a collaborative Notebook based environment with CPU or GPU based compute cluster. 
+- Customers who use Azure Databricks for advanced analytics can now use the same cluster to run automated machine learning experiments. 
+- You can keep the data within the same cluster. 
+- You can leverage the local worker nodes with autoscale and auto termination capabilities. 
+- You can use multiple cores of your Azure Databricks cluster to perform simultenous training. 
+- You can further tune the model generated by automated machine learning if you chose to. 
+- Every run (including the best run) is available as a pipeline. 
+- The model from the pipeline can be registered in Azure ML SDK workspace and then deployed to Azure managed compute (ACI or AKS) using the Azure Machine learning SDK.
+
+**Create Azure Databricks Cluster:**
+
+Select New Cluster and fill in following detail:
+ - Cluster name: _yourclustername_
+ - Cluster Mode: Any. **High Concurrency** preferred
+ - Databricks Runtime: Any 4.x runtime.
+ - Python version: **3**
+ - Workers: 2 or higher.  
+ - Max. number of **concurrent iterations** in Automated ML settings is **<=** to the number of **worker nodes** in your Databricks cluster.
+ - Worker node VM types: **Memory optimized VM** preferred. 
+ - Uncheck _Enable Autoscaling_
+
+
+It will take few minutes to create the cluster. Please ensure that the cluster state is running before proceeding further.
+
+**Install Azure ML with Automated ML SDK on your Azure Databricks cluster**
+
+- Select Import library
+
+- Source: Upload Python Egg or PyPI
+
+- PyPi Name (_with_ Automated ML capability): **azureml-sdk[automl_databricks]**
+
+- PyPi Name (_without_ Automated ML capability): **azureml-sdk[databricks]**
+
+- Click Install Library
+
+- Do not select _Attach automatically to all clusters_. In case you have selected earlier then you can go to your Home folder and deselect it.
+
+- Select the check box _Attach_ next to your cluster name
+
+(More details on how to attach and detach libs are here - [https://docs.databricks.com/user-guide/libraries.html#attach-a-library-to-a-cluster](https://docs.databricks.com/user-guide/libraries.html#attach-a-library-to-a-cluster) )
+
+- Ensure that there are no errors until Status changes to _Attached_. It may take a couple of minutes.
+
+**Note** - If you have the old build the please deselect it from cluster’s installed libs > move to trash. Install the new build and restart the cluster. And if still there is an issue then detach and reattach your cluster.
+
+**Now you can run the Automated ML sample notebook on your Azure Databricks cluster. Please let us know your feedback.**