# Anomaly Detection **Anomaly detection** can be performed using both supervised and unsupervised machine learning methods. Anomaly detection involves identifying rare items, events, or observations that differ significantly from the majority of the data. It's widely used in various applications, such as fraud detection, network security, fault detection in industrial systems, and more. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://digitalgarden.batamladen.com/notes/machine-learning/anomaly-detection.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.