Starting from a baseline architecture provided, I designed an improved deep net architecture to classify images of 100 categories that are a part of the cifar100 dataset. This was done using pytorch and improving on the baseline model by adding more layers (convolutional, pooling, ReLUs, fully-connected, and normalization).