Credit Card Fraud Detection

Tools: Python, scikit-learn, Pandas, Matplotlib, Seaborn

Built a machine learning model to detect fraudulent transactions in credit card datasets.

Workflow: EDA, Data Preprocessing (handling imbalance, scaling), Feature Selection, Model Training (classification models), and Evaluation (accuracy, precision, recall, F1-score, ROC-AUC).

Results: Achieved a robust fraud detection model capable of distinguishing between legitimate and fraudulent transactions, improving reliability and security in financial data.