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