Description
tldr: Classify cifar. Acheive performance similar to the state of the art. Classify
cifar. Achieve a top-5 accuracy of 80%.
Problem Statement Consider the cifar and cifar datasets which contain
32 × 32 pixel color images. Train a classifier for each of these with performance
similar to the state of the art (for cifar. It is your task to figure out what is state
of the art. Feel free to adapt any techniques from papers you read. I encourage you
to experiment with normalization techniques and optimization algorithms in this
assignment. Write a paragraph or two summarizing your experiments. Hopefully
you’ll be able to resuse your mnist program.