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Detecting Anomalies in Streaming Data, Evaluating Algorithms for Real-World Use
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| by Alexander Lavin Follow 0 Followers on Jun 01, 2016 |
32:32

Summary
Alexander Lavin introduces the Numenta Anomaly Benchmark (NAB), a framework for evaluating anomaly detection algorithms on streaming data.

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Bio

Alexander Lavin is a software and research engineer at Numenta, building machine intelligence by reverse-engineering the neocortex. He specializes in anomaly detection and natural language processing (NLP). Lavin studied mechanical engineering at Cornell and Carnegie Mellon Universities, focusing on spacecraft engineering.

Global Big Data Conference's vendor agnostic Global Data Science Conference is held on March 7th, March 8th & March 9th, 2016 on all industry verticals. The Conference allows practitioners to discuss data science through effective use of various data management techniques.

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