This repository presents a machine learning project focused on detecting anomalies in transaction data using multiple algorithms and evaluation techniques. The primary aim of this project is to ...

With vast numbers of transactions being processed daily, manual monitoring for suspicious activities is impractical. Machine learning algorithms, particularly anomaly detection techniques, can help ...

In this era of digital transformation, buzzwords like ‘Industry 4.0’ and ‘digitalization’ have become part of our daily vocabulary. But behind these trendy terms lies a potent technological innovation ...

These patterns often predicted edge device failures in advance at a 99% accuracy, allowing us to build self-healing systems that reduced downtime and manual intervention. While at AT&T, I was tasked ...

With the rapid development of blockchain technology, its applications in finance, supply chain management, the Internet of Things, and other fields have become increasingly widespread. However, the ...

In addition to stressing the need for updated risk assessments, the Supplemental Guidance specifically sets the expectation that institutions should have a layered security program that at a minimum ...

When inconsistent events occur, anomaly detection algorithms can isolate abnormal behavior and flag any events that do not correspond to the learned patterns. Such functionality is crucial in many ...