Really enjoyed visiting the Monetary Authority of Singapore (MAS) and talking on the applications of Deep Neural Networks for Natural Language Processing (NLP).
During the talk, there were some great questions from the audience, one of them was “can a character level model capture the unique structure of words and sentences? ” The answer is YES, and I hope that the demo, showing a three-layers 512-units LSTM model trained on publicly-available Regulatory and Supervisory Framework documents downloaded from the MAS website, predicting the next character and repeating it many times, helped to clarify the answer.
Training the same model on Shakespeare’s works and running both models side by side was fun!
TechnoFob 