Detect anomalies and outliers in datasets using ML algorithms like Isolation Forest, One-Class SVM, LOF, and autoencoders to identify unusual patterns. Generate Python code for custom anomaly detection tasks, including validation, error handling, performance metrics, insights, saved artifacts, and documentation.
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