Analyzing real life cases, it’s easy to notice that the issue of detecting anomalies is usually met in the context of various fields of application, including but not limited to intrusion detection, ...

What is explainable AI (XAI)? What are some of the use cases for XAI? What are the technology requirements for implementing XAI? Anomaly detection is the process of identifying when something deviates ...

There’s not a business out there that wouldn’t want to defend itself against fraudulent activities, hacking attempts, and operations disruptions. And with cases of fraud and cyberattacks on the ...

Anomaly detection is the process of identifying events or patterns that differ from expected behavior. Anomaly detection can range from simple outlier detection to complex machine learning algorithms ...

Machine-learning models are very good at anomaly detection when properly trained. These artificial-intelligence systems are currently used to identify people, places, and things for self-driving cars ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

In industry, the detection of anomalies such as scratches, dents, and discolorations is crucial to ensure product quality and safety. However, conventional methods rely on heavy computational ...

A good way to see where this article is headed is to take a look at the screenshot in Figure 1 and the graph in Figure 2. The demo program begins by loading a tiny 10-item dataset into memory. The ...

One key part of Microsoft’s big bet on machine learning is that these technologies need to be democratized, turned into relatively simple-to-understand building blocks that Microsoft’s developer ...