Building Production ML Monitoring from Scratch - Live Coding Session
MLOps World: Machine Learning in Production via YouTube
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Dive into a live coding session focused on constructing a cloud-native ML monitoring stack using open-source tools. Learn the fundamental principles of Machine Learning monitoring in production, then create a real-time web dashboard to measure model drift, feature statistics, and performance metrics. Explore how to integrate Python-based custom metrics into the dashboard. Follow along as Alon Gubkin, CTO of Aporia and experienced ML practitioner, guides you through the process of building a comprehensive monitoring solution for ML models in production. Gain hands-on experience in implementing essential monitoring techniques to ensure the reliability and performance of your machine learning models in real-world scenarios. Access the complete code on GitHub after the workshop to continue refining your ML monitoring skills.
Syllabus
Building Production ML Monitoring from Scratch Live Coding Session
Taught by
MLOps World: Machine Learning in Production