This repository contains a PyTorch implementation of a deep neural network for image classification on the CIFAR-10 dataset. The dataset consists of 60,000 32x32 color images in 10 classes, with 6,000 images per class. There are 50,000 training images and 10,000 test images.
The model achieves an accuracy of around 53% on the test set.
In order to run the notebook, you will need to have the following packages installed:
- PyTorch
- numpy
- matplotlib
The tutorial for the following notebook is obtained from Pytorch official tutorials.