Using Automated ML models in Azure Synapse Analytics
summary
Provisioned an Azure Synapse workspace and Spark pool, created an Azure Machine Learning workspace, loaded data into a Spark table from a notebook, and established a linked Azure Synapse and Azure ML workspaces connection. Kicks off an AutoML regression run (author notes runs can take ~3 hours), AutoML tries multiple algorithms, returns ranked models with explanations, and exposes the chosen model for batch scoring inside Synapse. Notes AutoML covers regression, classification, and time‑series but not every custom scenario.
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chapters (7)
- 0:00Introduction and agenda
- 3:44Understanding automated ML
- 11:51Azure synapse overview
- 18:01Integration strategy
- 20:25Technical demo
- 40:25Session wrap-up
- 42:50Q&A and closing
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