Detecting anomalies in unlabelled data

Tid: 26 maj 2021
Plats: OnlineSign up

The human brain is wired to detect anomalies. By looking at a data visualization we can spot a deviation and resonate around it. But humans don’t scale that well. So how can we translate human intuition to machines in order to detect anomalies?

In this Meetup on May 26 at 12-13 CEST (13-14 EEST) Federico Benzi will introduce some common approaches to anomaly detection. These techniques can be applied in a wide range of businesses, but in this presentation, we will focus on practical implementation in District Heating.

Dr. Federico Benzi is a Data Scientist with many years of Research and practical Data Science. The past months he has been working with a Research Program called BRAVA (Branschsamarbete för avancerad analys av värmedistribution och uppvärmningsbehov) that gathers Energy companies, Researchers and Data Scientists to better understand anomalies within District Heating.

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