In the digital era, Intrusion Detection is significant to improve cybersecurity using machine learning. It designs an intelligent intrusion detection system that leverages machine learning algorithms in detecting network anomalies and intrusions effectively. Preprocessing cleans, normalizes, and extracts features to enhance the quality of the dataset in order to make state-of-the-art algorithm. To exhibit the results as data using visualization techniques, by heatmaps, pair plots, and histograms. The metrics, such as accuracy, precision, recall, and F1-score considered for the performance evaluation. The proposed Django framework is implemented to develop web application which monitors, identifies network intrusions, and issue security alerts to ensure robust cybersecurity.