Image Classification using LeNet style architecture Dataset: CINIC-10 Used mini-batch size of 64, a learning rate of 0.001 and the ADAM optimizer Data Augmentation: enlarge the image by 10%, do a center crop by considering 90% of the image in the center, and flip the image.