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Report How to: Execute Anomaly Detection at Scale

How to: Execute Anomaly Detection at Scale

For Discovering Fraud, Networking Monitoring, Health Care, Uncovering Trends, and More.

As with most data science projects, the ultimate end goal or output of anomaly detection is not just an algorithm or working model. Instead, it’s about the value of the insight that outliers provide. That is, for a business, money saved from preventing equipment damage, money lost on fraudulent transactions, etc. In health care, it can mean earlier detection or easier treatment.

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Report Snap Shot

By the end of this guide, readers should have an
understanding of:

  • What anomaly detection is and how it differs from other similar systems
  • The three types of anomalies that can be detected
  • Use cases and examples of where anomaly detection is employed
  • How to build a basic anomaly detection system