Machine learning models can easily turn into a liability when they are unmonitored. When a model encounters unfamiliar data in real-world conditions, the result is often inaccurate predictions. These unreliable forecasts undermine consumer trust, introduce risk to the business, and invite regulatory scrutiny.
That’s why consistent model monitoring is so crucial to AI success.
In this session, we’ll show you how to use DataRobot’s intuitive tools to standardize model monitoring and management, automate time-consuming tasks, and improve collaboration between data science and IT departments.