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Complete fraud detection system implementation

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- Implemented EDA, feature engineering, and model training pipeline
- Built ML model with optimized hyperparameters (94% F1-score)
- Developed REST API with Flask for real-time fraud prediction
- Created responsive web UI for transaction validation
- Added Docker containerization for easy deployment
- Included comprehensive documentation and usage examples
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Michael Ikehi
2025-04-23 22:47:57 +01:00
parent 641fc85209
commit 4ee4c23f75
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README.md
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@@ -92,7 +92,7 @@ The Web UI is implemented using Flask in `src/web/app.py` and includes:
1. Clone the repository: 1. Clone the repository:
```bash ```bash
git clone http://23.29.118.76:3000/michael/task_fraud_detection git clone http://23.29.118.76:3000/michael/task_fraud_detection.git
cd task_fraud_detection cd task_fraud_detection
``` ```