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MapR : Anomaly Detection
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| par Ted Dunning le 10 juin 2014 |
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Résumé
The basic ideas of anomaly detection are simple. You build a model and you look for data points that don’t match that model. Building a practical anomaly detection system requires deal with practical details starting with algorithm selection, data flow architecture, anomaly alerting, user interfaces and visualizations.

Bio

Ted Dunning has been involved with a number of startups with the latest being MapR Technologies where he is Chief Application Architect working on advanced Hadoop-related technologies. He is also a PMC member for the Apache Zookeeper and Mahout projects.

Let's get together and chat about machine-learning, natural language processing, large scale data analytics using open source tools such as Hadoop MapReduce, Shark, NoSQL databases, the semantic web and linked data.

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