Introductory overview of time-series-based anomaly detection algorithms

Tutorial Slides by Andrew Moore

This simple tutorial overviews some methods for detecting anomalies in biosurveillance time series. The slides are incomplete: verbal commentary from the presentation has not yet been included as explanatory textboxes. Please let me (awm@cs.cmu.edu) know if you would be interested in more detail on these slides and/or access to the software that implements and graphs the various univariate methods. If I receive enough requests I will try to make both of the above available.

Download Tutorial Slides (PDF format)

Powerpoint Format: The Powerpoint originals of these slides are freely available to anyone who wishes to use them for their own work, or who wishes to teach using them in an academic institution. Please email Andrew Moore at awm@cs.cmu.edu if you would like him to send them to you. The only restriction is that they are not freely available for use as teaching materials in classes or tutorials outside degree-granting academic institutions.

Advertisment: I have recently joined Google, and am starting up the new Google Pittsburgh office on CMU's campus. We are hiring creative computer scientists who love programming, and Machine Learning is one the focus areas of the office. If you might be interested, feel welcome to send me email: awm@google.com .