You now have the ability to run your Azure Machine Learning service pipelines as a step in your Azure Data Factory pipelines. This allows you to run your machine learning models with data from multiple sources (more than 85 data connectors supported in Data Factory). The seamless integration enables batch prediction scenarios such as identifying possible loan defaults, determining sentiment, and analyzing customer behavior patterns. Get started quickly by creating an AzureMLService connection and AzureMLExecutePipelne activity to invoke your Azure Machine Learning pipelines in a Data Factory data pipeline.

Gaurav Malhotra joins Scott Hanselman to show how you can run your Azure Machine Learning (AML) service pipelines as a step in your Azure Data Factory (ADF) pipelines. This enables you to run your machine learning models with data from multiple sources (85 data connectors supported in ADF). This seamless integration enables batch prediction scenarios such as identifying possible loan defaults, determining sentiment, and analyzing customer behavior patterns.