As more and more machine learning models are deployed into production, it is imperative we have better observability tools to monitor, troubleshoot, and explain their decisions. In this talk, Aparna Dhinakaran, Co-Founder, CPO of Arize AI (Ex-Uber Machine Learning), will discuss the state of the commonly seen ML Production monitoring and its challenges. She will focus on how to use statistical distance checks to monitor features and model output in production, how to analyze the changes effects on models and how to use explainability techniques to determine if issues are model or data related.
