In this chapter, we will discuss how Recurrent Neural Networks (RNNs) are used for deep learning in domains where maintaining a sequential order is important. Our attention will be mainly devoted to text analysis and natural language processing (NLP), but we will also see examples of sequences used to predict the value of Bitcoins.
Many real-time situations can be described by adopting a model based on temporal sequences. For instance, if you think about writing a document, the order of words is important and the current word certainly depends on the previous ones. If we still focus on text writing, it is clear that the next character in a word depends on the previous characters (for example, The quick brown f... there is a very high probability that the next letter will be the letter o), as illustrated in the following figure. The key idea is to produce a distribution...
