anomaly outlier detection eggs in a tray

How to apply Unsupervised Anomaly Detection on bank transactions
 A use case of Unsupervised Learning with Python, step-by-step

In this tutorial, we’ll show how to detect outliers or anomalies on unlabeled bank transactions with Python.

You’ll learn:
– How to identify rare events in an unlabeled dataset using machine learning algorithms: isolation forest (clustering).
– How to visualize the anomaly detection results.
– How to fight crime with anti-money laundering (AML) or fraud analytics in banks
Use case and tip from people with industry experience

How to apply Unsupervised Anomaly Detection on bank transactions

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