Join us to discover how customers are using Fiddler for monitoring, explainability, and model analysis. MLOps Engineers and Data Scientists will get hands-on experience on how to instrument ML models with Fiddler for observability. Using a dedicated Fiddler cloud environment on AWS, we will register a model and publish model events into the Fiddler Model Performance Management platform.
We will use the insights surfaced by Fiddler to better understand data drift, data integrity, and underperforming cohorts. This should be a hot topic for customers driving critical ML initiatives and we hope to see you there.
Join us to discover how customers are using Fiddler for monitoring, explainability, and model analysis. MLOps Engineers and Data Scientists will get hands-on experience on how to instrument ML models with Fiddler for observability. Using a dedicated Fiddler cloud environment on AWS, we will register a model and publish model events into the Fiddler Model Performance Management platform.
We will use the insights surfaced by Fiddler to better understand data drift, data integrity, and underperforming cohorts. This should be a hot topic for customers driving critical ML initiatives and we hope to see you there.