Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. When it comes to artificial intelligence (AI), there's plenty to unpack—machine learning (ML ...

In his recent research, technology thought leader Lakshminarayana Reddy has introduced a state-of-the-art blueprint for addressing the ever-increasing risk of credit card fraud. The objective of his ...

Research published in the International Journal of Information and Communication Technology suggests that machine learning tools might be used to detect and so combat financial fraud. According to ...

Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

Amidst the ever-evolving landscape of data-driven industries, the battleground against fraud and money laundering remains relentless. However, a ray of hope emerges from the pioneering research of ...

Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed methods ...

Know why ML-driven anomaly detection is crucial for preventing malicious signature requests. Learn how machine learning identifies zero-day threats and secures crypto wallets.

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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, ...