DSE 730 Anomaly Detection

Credits: 3

The course will address anomaly detection in various types of data, ranging from single to high dimensionality, over a range of modalities. Topics will include current research developments in active and semi-supervised machine learning systems, including addressing the problems of developing high accuracy multi-class classifiers and finding rare, previously unknown classes in large datasets. The course will include both theory and a number of projects applying these techniques to a variety of real-world datasets.

Notes: This course is cross-listed with CSC 730.

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