TransferLab Training: Practical Anomaly Detection

This workshop introduces unsupervised ML techniques for anomaly detection, their strengths and weaknesses and different application areas.

Content

Identification of anomalies is of high interest in multiple industries for identifying safety and security risks, ensuring production quality, or finding new business opportunities. But anomalies are hard to detect because they are characteristically poorly represented in datasets.