ENGLISH

Practical Machine Learning: A New Look at Anomaly Detection

By Ted Dunning , Ellen Friedman

Book information

Publisher
O’Reilly Media
Year
2014
ISBN
978-1-491-90408-4
Language
english
Format
PDF
Filesize
21 MB (22161298 bytes)
Pages
66\66
Time added
2018-01-29 02:40:48
anomalyData MiningFraudMachine Learning

Description

Anomaly 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 examples 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 this report will help you tackle anomaly detection in your own project.

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