Simple image classification on the CIFAR-10 dataset using deep learning
Build a Deep Neural Network (Simple ANN and a CNN) to classify the images of the CIFAR 10 dataset into one of the 10 classes.
The CIFAR-10 dataset (Canadian Institute for Advanced Research, 10 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images.
The images are labelled with one of 10 mutually exclusive classes: airplane, automobile (but not truck or pickup truck), bird, cat, deer, dog, frog, horse, ship, and truck (but not pickup truck).
There are 6000 images per class with 5000 training and 1000 testing images per class.
The dataset is loaded directly from the tf.keras.datasets module.