DataRobot MLOps is the way to manage all your production models. In this demo, we walk through a typical day-in-a-life of a financial services company running a Center of Excellence for delivering ML in Production.
We'll see the types of administrative activities our MLOps engineer George performs, and understand how he works with Mary, our lead data scientist. George and Mary rely on each other to effectively build, deploy, and manage models for their company over their full lifecycle.
The demo covers:
Governed Approval Workflows
Monitoring (and troubleshooting) Service Health
Discovering the root cause of data drift and accuracy issues
Configuring humility rules
Importing models from GitHub to compare with the current production model i.e., champion/challengers
Finally, we will look at how easy it is for Ina our loan specialist to use the models George and Mary deliver. She does this using an automated AI application that Mary builds. This enables Ina to approve or deny loans with full confidence and trust in her decisions.