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This session will help you begin the journey to defining & implementing an ML Ops solution for your organization. We will begin with the metrics necessary for successful model lifecycle measurement, we will discuss the technology stack to be deployed and the operational model necessary for success at scale. These three must all be defined & built collectively to ensure alignment between operational needs, technology capabilities and success metrics. High model performance, elimination of bias and predictability are all key elements of our ML Ops strategy.

Speaker

JOEY jablonski

VP/Analytics, Pythian