Image-Classification-CNN

Neural networks and deep learning algorithms have been acknowledged for demonstrating their strengths in predicting multi-class outputs given original multi-dimensional inputs. This project attempts to create the optimal convolutional neural network for the CIFAR-10 dataset using the neural networks library Keras. A varying selection of filters, activation functions, pooling functions, and optimizers were tried for the learning algorithm. The functionality of each learning algorithm was determined using their corresponding test accuracies, and the algorithm that produced the highest test accuracy is considered to be the optimal convolutional neural network.