The project involved applying techniques like anomaly detection, pattern recognition, and classification models to uncover unusual transaction behavior and classify it effectively. I performed data preprocessing, feature selection, and model evaluation to ensure accurate and efficient detection.
🧠 Techniques Used:
Anomaly Detection | Pattern Recognition | Classification Models
🛠️ Tools & Technologies:
Python | Scikit-learn | Pandas
This project helped me understand the practical application of data science in financial security, enhancing my skills in building real-world ML solutions to detect fraud and minimize financial risk.