Speaker "Chris Fregly" Details Back



Waking the Data Scientist at 2am:  Detect Model Degradation on Production Models Using Amazon SageMaker Endpoints and Model Monitor


In this talk, I describe how to deploy a model into production and monitor its performance using SageMaker Model Monitor. With Model Monitor, I can detect if a model's predictive performance has degraded - and alert an on-call data scientist to take action and improve the model at 2am while the DevOps folks sleep soundly through the night.


Chris Fregly is a Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in San Francisco, California. He is co-author of the O'Reilly Book, "Data Science on AWS."
Chris is also the Founder of many global meetups focused on Apache Spark, TensorFlow, and KubeFlow. He regularly speaks at AI and Machine Learning conferences across the world including O’Reilly AI & Strata, Open Data Science Conference (ODSC), and GPU Technology Conference (GTC).
Previously, Chris was Founder at PipelineAI where he worked with many AI-first startups and enterprises to continuously deploy ML/AI Pipelines using Apache Spark ML, Kubernetes, TensorFlow, Kubeflow, Amazon EKS, and Amazon SageMaker.