In this project, we will attempt to build a character-level language model using an RNN to generate prose given some initial seed characters. The main task of a character-level language model is to predict the next character given all previous characters in a sequence of data. In other words, the function of an RNN is to generate text character by character.
To start with, we feed the RNN a huge chunk of text as input and ask it to model the probability distribution of the next character in the sequence, given a sequence of previous characters. These probability distributions conceived by the RNN model will then allow us to generate new text, one character at a time.
The first requirement for building a language model is to secure a corpus of text that the model can use to compute the probability distribution of various characters...
