Entity-Level ML Monitoring: Fine-Grained Anomaly Detection
When it comes to monitoring your ML models, the standard approach is to monitor the statistical behavior of entire datasets...
Essentially defined as the process of identifying outliers, this enables the detection of anomalies in the value of the metric in the inspected data and its value in a time period before the data was collected.