Fraud Detection ML Pipeline (Demo)

This project shows a simple demo of an end-to-end fraud detection machine learning pipeline using:

• Pandas for data processing
• Scikit-learn for model training
• Synthetic transaction data
• Feature engineering
• Train/test split and evaluation

This is a demo version based on typical fraud detection workflows (no real-world data).

Features

• Synthetic dataset creation
• Exploratory data analysis (EDA)
• Feature engineering
• RandomForest model
• Accuracy and confusion matrix

More files will be added soon.