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Obtain New Insights on Model Behavior with Fiddler

Posted Oct 11
# Fiddler
# Model Behavior
# Observability
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SPEAKER
Danny Brock
Danny Brock
Danny Brock
Solutions Engineer @ Fiddler AI

Danny is a senior solutions engineer at Fiddler. When you boil it down, this role is really about evangelizing the value of Fiddler to our prospects and customers through product demonstrations or evaluations with their own models and data. Danny has to understand the specifics around customer challenges to ensure they get maximum value from Fiddler.

Prior to Fiddler, Danny worked for a handful of startups in the analytics space like Endeca, Incorta, and Branchbird which was his own consulting company focused on Hadoop implementations.

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Danny is a senior solutions engineer at Fiddler. When you boil it down, this role is really about evangelizing the value of Fiddler to our prospects and customers through product demonstrations or evaluations with their own models and data. Danny has to understand the specifics around customer challenges to ensure they get maximum value from Fiddler.

Prior to Fiddler, Danny worked for a handful of startups in the analytics space like Endeca, Incorta, and Branchbird which was his own consulting company focused on Hadoop implementations.

+ Read More
SUMMARY

Discover how customers are using Fiddler for monitoring, explainability, and model analysis. MLOps Engineers and Data Scientists get hands-on experience on how to instrument ML models with Fiddler for observability. Using a dedicated Fiddler cloud environment on AWS, they register a model and publish model events into the Fiddler Model Performance Management platform.

We 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.

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