Anomaly Detection Algorithms

Anomaly detection algorithms identify unusual patterns or behaviors in data that differ significantly from the norm. Imagine monitoring a room of people; if suddenly someone starts acting strangely, you’d notice it as an anomaly. These algorithms analyze data from various sources, like transactions or sensor readings, to spot outliers that may indicate fraud, faults, or rare occurrences. By flagging these outliers, organizations can take action to investigate or mitigate potential issues, enhancing safety, security, and efficiency in various applications, from finance to healthcare.