CIFAR100-Classification-Challenge

This project applies machine learning and computer vision techniques to classify images from the CIFAR-100 dataset, which consists of 60,000 images spanning multiple categories, including everyday objects such as airplanes, cars, and animals. A residual network (ResNet) model was developed and optimized to predict the categories.