This was the first project I worked on during my internship. We received a large dataset containing transaction records of different credit card holders, and our goal was to detect potential fraudulent activities. The process began with data cleaning, followed by feature engineering. Then, we applied machine learning models such as Gradient Boosting and Random Forest, optimized their parameters, and finally created visual reports to present the results.