Outlier Detection with the Elastic Stack

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A common application of Machine Learning is to build models that can understand what's "normal" and what can be ignored, and it allows us to also see what is an interesting deviation from the norm. Is this deviation something we should be worried about or can we learn from it? The Elastic Stack includes a Machine Learning module which provides you with the infrastructure for running anomaly detection: running jobs, safeguarding data; storing, viewing and visualising the results.

Thank you to UTSA Open Cloud Institute and our speaker, Emanuil Tolev.

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