Online Payments Fraud Detection using Machine Learning

Built a Machine Learning system to detect fraudulent online payment transactions.

• Performed data cleaning and preprocessing on real-world financial dataset

• Conducted Exploratory Data Analysis (EDA) to understand fraud patterns

• Engineered features to improve model performance

• Trained multiple ML models (Logistic Regression, Decision Tree, etc.) using Scikit-learn

• Evaluated models using Accuracy, Precision, Recall, F1-score, and ROC-AUC

• Selected the best-performing model for fraud prediction

This project demonstrates strong skills in Data Science, Machine Learning, and problem-solving in real-world financial use cases.