A practical deep dive on production monitoring architectures for machine learning at scale using real-time metrics, outlier detectors, drift detectors, metrics servers and explainers.
Production Machine Learning Monitoring: Outliers, Drift, Explainers & Statistical Performance | by Alejandro Saucedo | Dec, 2020 | Towards Data Science In this article we present an end-to-end example showcasing best practices, principles, patterns and techniques around monitoring of machine learning models in production. We will cover standard… towardsdatascience.com |