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Finding outliers in your data

Our developer community monthly meet-up is back again. This one is for tech geeks. Dev ninjas. DevOps. Coding lovers. Creators. And you. In his talk, Floriano Zini, researcher at the Smart Data Factory of the Free University of Bozen-Bolzano, will introduce the main concepts of anomaly detection, present some machine learning algorithms to perform it, and provide some practical examples. Anomaly detection (aka outlier analysis) is a data mining technique to identify rare items, events, or observations that differ significantly from the majority of the data. Outliers typically correspond to some problem, such as a bank fraud, a structural defect, or a medical condition.