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.
With this accelerator notebook, you will:
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