Anomaly detection in machine learning is the identification of rarities; whether it be items, events or observations that stand out distinctly from the previously overwhelming majority of data. Anomalies, more popularly known as outliers, are a result of crucial actionable insights that require a systematic approach to be assumed such as system errors, security breaches or change in data patterns.

For more info: - https://macgence.com/blog/anomaly-detection-in-machine-learning/
Anomaly detection in machine learning is the identification of rarities; whether it be items, events or observations that stand out distinctly from the previously overwhelming majority of data. Anomalies, more popularly known as outliers, are a result of crucial actionable insights that require a systematic approach to be assumed such as system errors, security breaches or change in data patterns. For more info: - https://macgence.com/blog/anomaly-detection-in-machine-learning/
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Anomaly Detection in Machine Learning: Techniques, Applications, and Future Trends
Learn key techniques, challenges, and future trends in anomaly detection in machine learning. Perfect for data scientists and ML engineers.
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