This tutorial demonstrates how to use TensorFlow's Hub instead of the tf.data API for various tasks such as loading datasets, creating datasets from directories, data augmentation, and working with segmentation datasets. The text provides detailed explanations and code snippets for each task, showcasing how to handle different types of datasets using both tf.data and Hub. It also includes a discussion on the use of data augmentation in machine learning models.