Fraud Detection System using Isolation Forest

Developed an Anomaly Detection System to identify suspicious financial transactions using the Isolation Forest algorithm.

The project analyzes transaction data such as transaction amount and daily transaction count to detect unusual patterns that may indicate fraud.

The system demonstrates how machine learning can be used to automatically detect anomalies in financial datasets