(Part of an MLOps learning session series.)
Do you have machine learning models that are running outside of DataRobot? Is your organization using a set of diverse tools and platforms to deploy models, despite what IT wants? In this webinar we discuss how DataRobot can help manage ALL of your models regardless of where you deploy them; these include:
- Models runnings as stored procedures in a modern database.
- Models already in production, running on your infrastructure
- Models deployed to edge devices
This session will explore and demonstrate how DataRobot's MLOps agent framework allows anyone to monitor models deployed externally, to DataRobot MLOps platform. Using the agent frameworks enables you to monitor service health, predictions over time, data drift, etc., through the GUI or API.
In this session, we provide an overview of the MLOps agent framework and walk through some examples.
[video]
Hosts
- Timothy Whittaker (DataRobot, Customer Facing Data Scientist)
- Rajiv Shah (DataRobot, Customer Facing Data Scientist)
- Rewati Gautam (DataRobot, Use Case Engineer)
- Meghan Burns (DataRobot, DataRobot Community)
More Information
- If you’re a licensed DataRobot customer, search the in-app Platform Documentation for Managing Deployments and MLOps agent.
Let us know what you think!
Have questions not answered during the learning session? What to continue your conversation with Tim, Rajiv, and Rewati? Post Your Comment here or send email to learning_sessions@datarobot.com. We're looking forward to hearing from you!
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