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Anomaly Detection

Get to anomaly detection faster with Cloudera's Applied Machine Learning Prototypes

The Applied Machine Learning Prototype (AMP) for anomaly detection reduces implementation time by providing a reference model that you can build from. Built by Fast Forward Labs, and tested on AMD EYPC™ CPUs with Dell Technologies, this AMP enables data scientists across industries to truly practice predictive maintenance.

Memory Anomaly Detection in N|Solid [5/10] The best APM for Node, layer by layer

Anomaly detection refers to the problem of finding patterns in data that do not conform to expected behavior. Understanding memory management reduces the possibility of wasting your application's resources and the unexpected effects on performance. According to Sergey Kibish, Anomalies can be illustrated in a simple two-dimensional space.


How to use anomaly detection and machine learning together

Anomaly detection can be essential to identifying potential incidents using data—including fraud detection, intrusion and security alerts, manufacturing quality control, and medical diagnostics. Flexible and powerful, anomaly detection is an important part of the analyses you’ll need to track and optimize business operations.


Gain Business Value With Big Data AI Analytics

“Data-driven” is the latest buzzword in organizations in which data-based decision making is directly connected to business success. According to Gartner’s Hype Cycle, more than 77% of the C-suite now say data science is critical to their organization meeting strategic objectives. For top organizations looking to adopt a data-driven culture to stay competitive, what does that mean?


Why anomaly detection is important

Anomaly detection does not have the same gravitas as big data buzzwords like machine learning, advanced analytics, and decision support systems, all of which are becoming household names in the business world. But anomaly detection is just as relevant, if not more important, to a thriving business intelligence system, and ultimately, the bottom line. What is anomaly detection?