This repository supports the paper "Breaking out of the interpretability asylum using social sciences and coffee plates as battering ram.". The code can be found in the file code.ipynb and images used are in the compressed file images/data_2.zip.
GradCam produces visual explanations by highlighting areas central to the decision making. Read more about GradCam in the paper "Grad-cam: Visual explanations from deep networks via gradient-based localization" written by Selvaju et al. The Grad-CAM implementation is based on this paper.
For machine learning part of the work we used the framework by Fast.ai.