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Unsupervised Anomaly Detection || Elena Sharova



This talk will focus on the importance of correctly defining an anomaly when conducting anomaly detection using unsupervised machine learning. It will include a review of Isolation Forest algorithm (Liu et al. 2008), and a demonstration of how this algorithm can be applied to transaction monitoring, specifically to detect money laundering.

EVENT:

PyData London 2018

SPEAKER:

Elena Sharova

PERMISSIONS:

PyData provided Coding Tech with the permission to republish this video.

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