Real Enough Time Processing and Bayesian Banditry
Channel: Jim Scott
Date: 25/08/2014

Ted Dunning provides a basic introduction to Storm and describes a simple aggregation application.  In addition, Ted shows how Storm can be used to do completely real-time machine learning.  In such a learning application, the classification algorithm makes decisions which affect which data the algorithm gets to use as training data.  The Bayesian Bandit is a recent algorithm which provides state-of-the-art performance but which is exceedingly simple. This presentation was given on April 24th, 2012 at the AllState in Northbrook, IL.

To view this presentation on slideshare: http://www.slideshare.net/ChicagoHUG/real-enoughtime-processing-chug-2012024