Practical Machine Learning: a New Look at Anomaly Detection

Name: Practical Machine Learning: a New Look at Anomaly Detection
Price: 21.63 USD
Availability: InStock
ISBN: 9781491911600

ISBN-10: 1491911603

ISBN-13: 9781491911600

Edition: 2014

Authors: Ted Dunning, Ellen Friedman

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Description:

Finding What You Don't Know to Look ForAnomaly detection is the detective work of machine learning: finding the unusual, catching the fraud, discovering strange activity in large and complex datasets. But, unlike Sherlock Holmes, you may not know what the puzzle is, much less what “suspects” you’re looking for. This O’Reilly report uses practical example to explain how the underlying concepts of anomaly detection work.From banking security to natural sciences, medicine, and marketing, anomaly detection has many useful applications in this age of big data. And the search for anomalies will intensify once the Internet of Things spawns even more new types of data. The concepts described in…

Book details

Copyright year: 2014
Publisher: O'Reilly Media, Incorporated
Publication date: 8/22/2014
Binding: Paperback
Pages: 66
Size: 5.98" wide x 8.94" long x 0.39" tall
Weight: 0.308
Language: English

Sean Owen has been a practicing software engineer for 9 years, most recently at Google, where he helped build and launch Mobile Web search. He joined Apache's Mahout machine learning project in 2008 as a primary committer and works as a Mahout consultant.Robin Anil joined Apache's Mahout project as a Google Summer of Code student in 2008 and contributed to the Classifier and Frequent Pattern Mining packages with algorithms that run on the Hadoop Map/Reduce platform. Since 2009, he has been a committer at Mahout and works as a full-time Software Engineer at Google.