CIFAR10 Classification
This project aims to classify images from the CIFAR-10 dataset using deep learning techniques. The dataset consists of 60,000 32x32 color images in 10 classes, with 6,000 images per class. The goal is to classify each image into its corresponding class.
The CIFAR-10 dataset can be downloaded from the official website, or through the Tensorflow and Keras librares. It is split into a training set of 50,000 images and a test set of 10,000 images. Each image is a 32x32 pixel RGB image, with 3 color channels.