Train supervised models on labeled datasets to accurately differentiate between legitimate and fraudulent transactions..Preprocess transaction data by normalizing features and encoding categories to improve fraud detection model performance..Use Random Forests and Neural Networks to effectively identify complex fraud patterns in financial transactions..Evaluate model performance using precision, recall, and F1-score metrics to ensure fraud detection accuracy..Deploy fraud detection models in real-time systems to monitor and block suspicious transactions instantly..Read More Stories