Azure ML Designer has been an excellent tool that allows business users to intuitively build machine learning pipelines.
Currently, many business-user-oriented capabilities in Azure ML are no longer being updated, while Fabric is making significant advancements in this area.
Proposal:
Similar to Fabric Notebooks and Data Pipelines, enable drag-and-drop selection of data from OneLake, followed by data splitting and ML model creation through algorithm selection in a GUI
mlflow integration so that execution results (metrics, logs, models) from ML pipelines created in Fabric can be sent to external mlflow servers (e.g., Azure ML)
Copilot integration to automatically generate machine learning pipelines from natural language instructions
This would allow business users to seamlessly build machine learning workflows entirely within Fabric, significantly reducing the time from data to business value.
ToddChitt
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