Network Intrusion Detector

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The Network Intrusion Detector is a binary classification machine learning model, built using a series of convolution kernels and max pooling layers, trained on the KDD Cup 1999 dataset. The model seeks to distinguish between well-intentioned and malicious network connections, and identify which is which. The model has an ROC curve of 1.0, and generalized extremely well to the test data, even with a 25%/75% training/test split, and as a result, is highly accurate.