This project implements a Network Intrusion Detection System (NIDS) using various machine learning algorithms to classify network traffic as either normal or anomalous (intrusion). The system utilizes preprocessing techniques, feature encoding, and model evaluation metrics to identify intrusions with high accuracy.
The dataset for this project was sourced from Kaggle.