Understanding Convolutional Neural Networks through Visualizations in PyTorch

In the present era, machines have successfully achieved 99% accuracy in understanding, identifying the features and objects in the images. We see them daily, to quote a few, smartphones recognizing faces in the camera, ability to search particular photos in google photos, scanning text from the barcode or books at a good pace etc. This state of the art performance of the machine was possible because of a specific type of neural network called Convolutional Neural Network, also known as convnet. If you are a deep learning enthusiast, you would have probably heard about these and you might have developed a few image classifiers. Modern deep-learning frameworks like Tensorflow and PyTorch make it easy to teach machines about images.