Unsupervised Learning Using TensorFlow 2

In this chapter, we will investigate unsupervised learning using TensorFlow 2. The object of unsupervised learning is to find patterns or relationships in data in which the data points have not been previously labeled; hence, we have only features. This contrasts with supervised learning, where we are supplied with both features and their labels, and we want to predict the labels of new, previously unseen features. In unsupervised learning, we want to find out whether there is an underlying structure to our data. For example, can it be grouped or organized in any way without any prior knowledge of its structure? This is known as clustering. For example, Amazon uses unsupervised learning in its recommendation system to make suggestions as to what you might like to buy in the way of books, say, by identifying genre clusters in your previous...