Unleash Your Model's Potential: Guide to Deploying a Fabric ML Model on Azure ML Inference Endpoint

Microsoft Fabric's Data Science workload leverages Synapse ML for training and are ideally suited to enrich data stored in a data lake. But models developed in Fabric can also be deployed in other environments like Azure Machine Learning to take advantage of real-time inference endpoint deployment and other techniques. This video walks through the steps to export a model from Fabric, Import it into an Azure ML workspace, and deploy it to a real-time inference endpoint. This video is a walk-through of the process described in this blog post: https://robkerr.ai/deploying-fabric-ml-models-to-azure-ml/ Note: Microsoft has inference endpoint support on the Fabric roadmap as of this recording. If you're reading this after Q2/2024 check whether Fabric natively supports inference endpoint deployment as another option to the techniques covered here. 0:00 Introduction 0:49 Export Model from Fabric 2:17 Import Model to Azure ML 3:03 Create a real-time inference endpoint 3:57 Test the endpoint within Azure ML 4:24 Test the endpoint from Postman 6:11 Summary