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Anomaly Detection Techniques in ML by srivastawapooja45 is a document available to read on EtoBox.

Anomaly detection is a technique for identifying patterns in data that deviate from expected behavior, useful in various domains such as cybersecurity. It includes types of anomalies like point, contextual, and collective anomalies, and employs methods like statistical techniques, machine learning algorithms, and deep learning. Autoencoders, a type of neural network, are used for unsupervised learning and can aid in anomaly detection by reconstructing input data, while feature learning automates the discove

Author

srivastawapooja45

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EN