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Appledore research paper: Machine learning to improve anomaly detection


The telecommunications network operations center processes billions of events daily. In most cases, events that violate service level agreements and cause widespread network outages occur because of the complexity to accurately identify, isolate, and detect the root cause.

In this paper, you’ll learn how machine learning (ML) can be used to tackle these challenges within networks and explore the potential it has to improve customer satisfaction through reducing mean time to resolution (MTTR) and lowering operational costs by offloading outlier detection to machines and not humans.