Credit Card Fraud Detection Using ML This project detects fraudulent transactions using ML. Challenges include class imbalance, data privacy, and evolving scams. We apply SMOTE, Random Forest, and XGBoost, optimizing precision, recall, and ROC-AUC for real-time fraud detection.