Visualization for Sequence Models for Debugging and Fun
Visual analysis is a great tool to explore deep learning models when there is no strong mathematical hypothesis yet available. I will present two visual tools where we used design study methodology to allow exploration of patterns in hidden state changes in RNNs/LSTMs (LSTMVis) and exploration of Sequence2Sequence models (Seq2Seq-Vis). Both model types have shown superior performance for NLP like language modeling or language translation. Examples about both tasks will be shown on a variety of models.
As beautiful distraction, we also utilize data science methods to investigate large data in a more artistic way. Formafluens is such a data experiment where we analyze a large collections of doodles made by humans in the Google Quickdraw tool.