Credit Card Fraud Detection
Trained a binary classifier on 284,807 transactions using Python, scikit-learn, Pandas, and SMOTE. Achieved 85% accuracy, reduced false positives by 15% through SMOTE resampling and GridSearchCV tuning, and achieved an F1-score of 0.88 on the fraud minority class.