Patrick Gadd trains a deep neural network to generate new fonts. To do so he uses bigrams, pairs of characters, encoded as one-hot vectors and so called style vectors, that represent fonts as his networks inputs. After training he can interpolate the font style of his bigrams between existing fonts. He then added an algorithm to combine the bigrams into full words. Well written article on how to encode characters and fonts for your neural net and the source code is included.