kkrusere / Credit-Card-Fraud-Anomaly-Outlier-Detection

The project explores a range of methods, including both statistical analysis, traditional machine learning and deep learning approaches to anomaly detection a critical aspect of data science and machine learning, with a specific application to the detection of credit card fraud detection and prevention.

Credit Card Fraud (Anomaly/Outlier) Detection

The processes of determining an entry among entries that does not seem to belong. In this case we are using the Anonymized Credit Card dataset from Kaggle, which has transactions labeled as fraudulent or genuine to create an ML Fraud Detection model.

Project Contributors: Kuzi Rusere
MBA streamlit App URL: N/A