While working on my undergrad thesis on relation classification of biomedical text using deep learning methods, I quickly hacked together models in Tensorflow that combined convolutional and recurrent layers in various combinations. While some of these “network architectures” worked superbly (even surpassing state-of-the-art results), I had no clue what was happening inside the model. To gain such an intuition, I read about 20 recent papers on text classification (starting with the first “CNN for sentence classification” paper by Yoon Kim) over the course of a week.