In this accelerator , we walk through how to work with Snowflake as a data source and DataRobot's Python API 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.


What you will learn  

  • Connect to DataRobot
  • Import data from Snowflake into DataRobot
  • Create a DataRobot project and run AutoML 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


Additional Resources

Reference DataRobot's API documentation

Version history
Last update:
‎09-05-2023 10:26 PM
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