tph-kds/anomaly_detection_in_transactions

This project aims to detect fraudulent transactions by leveraging machine learning-based anomaly detection techniques, and to develop an automated system that can monitor transactions in real-time, identify anomalies, and flag potential fraudulent transactions for further investigation.

24
/ 100
Experimental

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 3 / 25
Maturity 9 / 25
Community 12 / 25

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Stars

3

Forks

1

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Nov 08, 2024

Commits (30d)

0

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