Execute Azure Machine Learning pipelines in Azure Data Factory and Synapse Analytics

As more companies are deploying Machine Learning models using Azure, they start to think about how to integrate Azure Machine Learning and Azure Synapse Analytics.

Run your Azure Machine Learning pipelines as a step in your Azure Data Factory and Synapse Analytics pipelines. The Machine Learning Execute Pipeline activity enables batch prediction scenarios such as identifying possible loan defaults, determining sentiment, and analysing customer behaviour patterns.

This link below will explain how to do it, the below video features a six-minute introduction and demonstration of this feature.

Execute Azure Machine Learning pipelines — Azure Data Factory & Azure Synapse | Microsoft Docs

Create a Machine Learning Execute Pipeline activity with UI

To use a Machine Learning Execute Pipeline activity in a pipeline, complete the following steps:

1. Search for Machine Learning in the pipeline Activities pane, and drag a Machine Learning Execute Pipeline activity to the pipeline canvas.
2. Select the new Machine Learning Execute Pipeline activity on the canvas if it is not already selected, and its Settings tab, to edit its details.

3. Select an existing or create a new Azure Machine Learning linked service, and provide details of the pipeline and experiment, and any pipeline parameters or data path assignments required for the pipeline.