Anomaly detection. Many people speak about it, some use it, some build it, some love it. . .but many hate it. Pieter Buteneers offers an overview of this strange beast and explains why you should use it.
Pieter shares his experiences developing an anomaly detection system for CoScale, outlining the methods he used, tested, and dismissed and covering what worked, what didn’t, and why. Pieter explores in detail the difference between statistical significance and relevance, why the univariate approach is the way to go, why most multivariate techniques don’t work, and why you should keep it simple, stupid.
Some of you will try more complex techniques. And you should. But not before you know how to use them without them misleading you.
Pieter Buteneers is a data strategist and machine learning consultant at CoScale. Pieter is relatively new to the DevOps field. Previously, he was a postdoc at Ghent University, where he did research on AI, machine learning, and deep learning. Pieter has also given a TEDx talk (on a somewhat unrelated subject).
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