10446: When is an Anomaly a Problem? Identifying the Meaning Behind Using Machine Learning to Identify Operational Anomalies
Project and Program:
Service Delivery,
Operations Management & Automation
Tags:
Proceedings,
SHARE Orlando 2024,
2024
As the volumes of operational data continue to exponentially expand, the need
for using machines to interpret data is critical The use of machine learning to
identify operational anomalies is becoming more pervasive. Understand the logic
and key decisions when using machine learning to identify when an anomaly is a
problem and not just something that is different. -- Presented by Daniel Wiegand; Tim Brooks
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