In this example, we will be working on one of the most extensively used datasets in image comprehension, one which is used as a simple but general benchmark. In this example, we will build a simple CNN model to have an idea of the general structure of computations needed to tackle this type of classification problem.
This dataset consists of 40,000 images of 32x32 pixels, representing the following categories: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck. In this example, we will just take the first of the 10,000 image bundles to work on.
Here are some examples of the images you can find in the dataset:
We must ...