Credit Card Fraud Detection with accuracy 99%

This project aims to detect fraudulent credit card transactions using various machine learning models. It includes extensive data preprocessing, feature scaling, encoding, and the use of both traditional and ensemble classifiers. Models such as Random Forest, Decision Tree, SVM, KNN, CatBoost, and LightGBM are trained and evaluated using multiple performance metrics