Machine Learning Monitoring in Production - Lessons Learned from 30+ Use Cases

Explore practical insights on machine learning monitoring in production environments, drawing from over 30 real-world use cases. Learn why traditional software monitoring practices fall short for machine learning stacks and discover effective strategies for real-time issue detection and alerting. Gain valuable knowledge on essential metrics to implement, their prioritization, and whether existing monitoring tools suffice or if an MLOps platform is necessary. Led by Lina Weichbrodt, a Lead Machine Learning Engineer with extensive experience in developing scalable ML models for production, this 56-minute talk offers a comprehensive guide to enhancing your machine learning monitoring capabilities.

Machine Learning Monitoring in Production: Lessons learned from 30+ Use Cases