Traffic Sign Classifier

The goal of this project was to build a simple neural network model capable of classifying German traffic signs using a convolutional network built on the Lenet-5 architecture. This is achieved by having a dataset of labeled traffic signs and preprocessing the training set to prepare the model to be trained. The model is then cross tested on a dev or valid set and tuning hyperparameters until a prediction accuracy of over 95% was achieved.