Network Traffic Anomaly Detection using PCA and Isolation Forest This project demonstrates using PCA for dimensionality reduction and Isolation Forest for detecting anomalies in network traffic data. It includes data simulation, model training, anomaly prediction, and visualization to identify suspicious activities in network traffic.