A simple implementation of a recurrent neural network (in plain python) designed to learn the writing style of an author. Borrows heavily from textbooks and other sources, with support for character and word based tokenization. A Keras based implementation is also provided. This is far from the best approach (network design, stack, etc.) for this particular task, but tweaking network implementations can be a helpful way to explore how they function.
Recurrent Neural Network Source Code (Python)
When training with the complete works of Shakespeare, this network produces results such as the following, after a few epochs:
Two are pardoned a life, that every clap is his church. Who, wherefore are I to be endured for thus depart, your Roman suns. You be strange haste, that I royal caterpillars coward. 'Tis make which gold, being unto the counterpoise, harmless We'll nuptial once, to suck disobedience And clapp'd positively sometime comes. But fell not no thing must be but your consequence; monstrous John? To given I live in array, hearts, And not in the arms than I that hath March I could but hear you encounter it, In our brothers Oxford now but Edward, say'st? Speak thou go. They I come
Visit Andrej Karpathy's post about recurrent neural networks for a deep dive into how these kinds of networks operate.
