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On-premise users: click in-app to access the full platform documentation for your version of DataRobot.

End-to-end ML workflow with Snowflake

Access this AI accelerator on GitHub

This AI accelerator walks through how to work with Snowflake (as a data source) and DataRobot's Python client to import data, build and evaluate models, and deploy a model into production to make new predictions. More broadly, the DataRobot API is a critical tool for data scientists to accelerate their machine learning projects with automation while integrating the platform's capabilities into their code-first workflows and coding environments of choice.

By using this accelerator, you will:

  • Connect to DataRobot.
  • Import data from Snowflake into DataRobot.
  • Create a DataRobot project and run Autopilot.
  • Select and evaluate the top performing model.
  • Deploy the recommended model with MLOps model monitoring.
  • Orchestrate scheduled batch predictions that write results back to Snowflake.

Updated September 28, 2023
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