Image recognition for cfar dataset The goal of this assessment is to get hands-on experience designing and training deep convolutional neural networks using PyTorch. Using a baseline architecture, I designed an improved deep net architecture to classify (small) images into 100 categories, achieving a 63.3% accuracy. This is part 1