Hello MNIST: Implementing our first AutoKeras experiment

Our first experiment will be an image classifier using the MNIST dataset. This MINST classification task is like the "hello world" of DL. It is a classic problem of classifying images of handwritten digits into 10 categories (0 to 9). The images come from the MNIST, the most famous and widely used dataset in ML. It contains 70,000 images (60,000 for training and 10,000 for testing) collected in the 1980s by the NIST.

In the next screenshot, you can see some samples of every number in the MNIST dataset:

Figure 2.10 – MNIST dataset sample images

AutoKeras is designed to easily classify all types of data inputs—such as structured data, text, or images—as each of them contains a specific class.

For this task, we will use ImageClassifier. This class generates and tests different models and hyperparameters, returning an optimal classifier to categorize the images of handwritten...