Assignment 2a
Points:
- Anomaly Detection: 50 points equally distributed between the tasks quoted. Please note that the Guided Grad-CAM subtask only applies to the specific sections CS370-Honors and CS-GY-6613.
Points:
In the cats vs dogs classification task we trained a model benefiting from data augmentation that has achieved a certain level of accuracy without overfitting the data. Your task here is to provide the implementation of explainer algorithms to understand the model’s decision-making process. After you watch the video, insert in the cells elow your code below that implement two methods:
It is strongly advised (unless you are already have expertise in Keras/TF) to implement the assignment with Pytorch and Captum. You are free to use the high-level APIs of the framework of your choice.
Your notebook should include markdown cells that describes the explainer method in a tutorial fashion (so that anyone that knows just how CNNs work should be able to understand) and the results of each explainer algorithm.
Source: CNN Explainers