CIFAR-10 is a labeled datasetcontaining 60,000 images. It contains ten classes: airplane, automobile, bird, cat, deer,dog, frog, horse, ship, and truck. Each class contains exactly 6,000 images in which the dominantobject in the image is of that class. The classes are completely mutually exclusive. There is nooverlap between automobiles and trucks. For instance, Automobile includes sedans, SUVs, andother small vehicles while Truck includes bigger trucks. Neither includes pickup trucks. The restof this report is organized as follows.
This project implements a thee layer convolutional neural network to classify the CIFAR-10 dataset using the TensorFlow.