Ted Dunning View Bio
Anomaly detection is the art of automating surprise. To do this, we have to be able to define what we mean by normal and recognize what itmeans to be different from that.
The basic ideas of anomaly detection are simple. You build a model and you look for data points that don’t match that model. The mathematical underpinnings of this can be quite daunting, but modern approaches provide ways to solve the problem in many common situations.
Ted will describe these modern approaches with particular emphasis on several real use-cases including:
a) rate shifts to determine when events such as web traffic, purchases or process progress beacons shift rate
b) time series generated by machines or biomedical measurements
c) topic spotting to determine when new topics appear in a content stream such as Twitter
d) network flow anomalies to determine when systems with defined inputs and outputs act strangely.
In building a practical anomaly detection system you have to deal with practical details starting with algorithm selection, data flow architecture, anomaly alerting, user interfaces and visualizations. Ted will show how to deal with each of these aspects of the problem with an emphasis on realistic system design.
Ted Dunning is Chief Application Architect at MapR Technologies and committer and PMC member of the Apache Mahout, Apache ZooKeeper, and Apache Drill projects. Ted has been very active in mentoring new Apache projects and is currently serving as vice president of incubation for the Apache Software Foundation. Ted was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems. He built fraud detection systems for ID Analytics (later purchased by LifeLock) and he has 24 patents issued to date and a dozen pending. Ted has a PhD in computing science from the University of Sheffield. When he’s not doing data science, he plays guitar and mandolin. He also bought the beer at the first Hadoop user group meeting..