Detecting Credit Card Fraud with Machine Learning

This project was conducted in partnership with anonymous banking insitution and the PIC Math program.

We analyzed a large dataset of credit card transactions to identify fraudulent activity. By implementing and comparing Random Forest and K-Nearest Neighbors (KNN) algorithms in Python, we achieved high accuracy in detecting anomalies. We recieved a reating of excellent from the PIC Math committee for our report.

• Tools: Python, Pandas, Scikit-Learn, Matplotlib
• Outcome: Delivered a comprehensive report and presentation to industry partner’s cybersecurity team.