Anomaly Detection and Machine Learning refer to the use of AI techniques to identify unusual patterns or behaviors in data that deviate from expected norms. Machine learning models analyze historical data to learn normal patterns and automatically detect outliers or irregularities. These anomalies may indicate system failures, fraud, security breaches, or performance issues. The process improves over time as models continuously learn from new data. It is widely used in cybersecurity, IT monitoring, finance, and industrial systems. This approach enables proactive issue detection, faster response, and improved system reliability.
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