Keeping Up With ML Models in Production: Mitigating Performance Drift

Explore strategies for maintaining machine learning model performance in production environments during this 33-minute conference talk from MLOps World: Machine Learning in Production. Discover the challenges of performance drift and changing data distributions that impact deployed models over time. Learn practical approaches to mitigate these effects, illustrated through a sample prediction task. Gain insights from real-world experience in deploying and monitoring production-grade ML pipelines for predictive maintenance. Examine often-overlooked aspects of machine learning implementation, including collaborating with non-technical team members and integrating ML within agile frameworks. Equip yourself with valuable knowledge to keep your ML models performing optimally in real-world production scenarios.

Catch Me If You Can: Keeping Up With ML Models in Production