batch endpoint jobs - mltable note

Author: s-polly

articles/machine-learning/how-to-access-data-batch-endpoints-jobs.md

@@ -341,7 +341,7 @@ The following examples show how to create jobs while taking data inputs from [da
 Azure Machine Learning data assets (formerly known as datasets) are supported as inputs for jobs. Follow these steps to run a batch endpoint job that uses input data that's stored in a registered data asset in Azure Machine Learning.
 
 > [!WARNING]
-> Data assets of type table (`MLTable`) aren't currently supported.
+> Data assets of type table (MLTable) aren't currently supported for model deployments. MLTable is supported for pipeline component deployments.
 
 1. Create the data asset. In this example, it consists of a folder that contains multiple CSV files. You use batch endpoints to process the files in parallel. You can skip this step if your data is already registered as a data asset.