Credit Card Fraud Detection

• Github URL: Project Link

Analyzed credit card transaction data to detect fraudulent activities using machine learning models in Python on Google Colab.

Tackled challenges like outlier analysis, highly imbalanced class distributions, and detecting rare fraud patterns.

Implemented models including Logistic Regression, KNN, Decision Tree, and Random Forest, using SMOTE to address class imbalance and enhance performance.

Conducted univariate, bivariate, and multivariate analyses for data visualization and achieved the best results with Logistic Regression after evaluating ML metrics and precision-recall trade-offs.