Visualizing Convolution Neural Networks using Pytorch

Convolution Neural Network (CNN) is another type of neural network that can be used to enable machines to visualize things and perform tasks such as image classification, image recognition, object detection, instance segmentation etc…But the neural network models are often termed as'black box' models because it is quite difficult to understand how the model is learning the complex dependencies present in the input. Also, it is difficult to analyze why a given prediction is made during inference. These methods help us to understand what does filter learn? Citation Note: The content and the structure of this article is based on the deep learning lectures from One-Fourth Labs -- PadhAI. If you are interested checkout there course.