Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...

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, ...

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 ...

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 can be powerful in spotting cyber incidents, but experts say CISOs should balance traditional signature-based detection with more bespoke methods that can identify malicious activity ...

Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...