Welcome to the repository dedicated to exploring different methods of Anomaly Detection. This repository serves as a centralized hub for various work, research, and resources related to Anomaly Detection.
Anomaly detection is a technique used in data mining and machine learning to identify patterns that do not conform to expected behavior, called anomalies, outliers, or novelties. The goal is to find data points significantly different from most of the data. Anomalies could indicate critical incidents such as fraud, network intrusions, medical problems, or structural defects.
Some of the techniques for detecting anomalies are given below:
For questions, suggestions, or collaborations, feel free to reach out to the repository owner [email protected]
Happy Coding!