DataRobot API resources > AI accelerators > Ecosystem integration templates > End-to-end ML workflow with Snowflake

End-to-end ML workflow with Snowflake¶

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.