ML Monitoring in Under 5 Minutes

In this article, the author demonstrates how to set up data logging and machine learning (ML) monitoring using open-source tools whylogs and WhyLabs. The process involves installing whylogs, importing necessary libraries, creating a dataset profile, setting up access keys for WhyLabs, writing profiles to the AI observatory platform, and enabling pre-configured monitors to detect anomalies in data quality, data drift, and model performance. Additionally, the author explains how to separate model inputs and outputs and monitor performance metrics such as accuracy and precision. The article also provides links to example notebooks for classification and regression monitoring on GitHub.