Visibility and Monitoring for Machine Learning Models

In this talk, Josh Willis, an engineer at Slack and former Director of Data Science at Cloudera, discusses the importance of testing machine learning models in production. He emphasizes that deploying a machine learning model is not like deploying regular code patches and should be done repeatedly to ensure optimal performance. Willis also highlights the differences between lab data scientists and factory data scientists, noting their respective failure modes for machine learning. Additionally, he recommends reading "What's your ML test score? A rubric for production ML systems" as a guide for deploying machine learning models into production.