Presenting MapR's Sr Architect Ted Dunning: Data Science & Business Intelligence

5:00 Networking, Food and Drinks, courtesy of Aaron's

6:00 Presentation

7:00 Demos Q&A

7:00 More networking

Ted Dunning - Chief Application Architect, MapR

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 (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.

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How to Find What You Didn't Know to Look For, Practical Anomaly Detection
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 it means 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.

We 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.
We will show how to deal with each of these aspects of the problem with an emphasis on realistic system design.

Sponsored by:

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Aaron's

Aaron's is excited to sponsor this event with our technology partner MapR. Please join us at our new Technology Studio in Kennesaw. End your day a little early and come join us for food, networking and learning.

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Anova Analytics is a Data Science partnership focused on advanced Data Driven Decision support using predictive and prescriptive analytics technology. We combine math and science to create innovative and superior business and industrial solutions for our clients. Our scientific expertise includes statistical algorithms, machine learning, neural networks, and intelligent systems. Our scientists have a proven record in producing effective predictive models to extract hidden patterns, deliver efficient and robust decision support solutions. This is complemented by our Data Driven Analytics framework for rapid agile execution of predictive models and rules.