Detecting Neptune Attacks in Network Activity Using Random Forest

This code preprocesses network activity data, standardizes column names, verifies the target column, and encodes categorical variables using one-hot encoding. It ensures feature alignment between training and test sets, handles missing values, and separates features and target variables. The Random Forest classifier is trained, evaluated using a validation set, and used to predict Neptune attacks in the test set. Predictions are saved to a CSV file for further analysis.