Data Augmentation for Image Classification

This repository demonstrates various data augmentation techniques for improving image classification models. It includes transformations such as rotation, flipping, scaling, and cropping to artificially increase the diversity of the training dataset. The project uses these techniques in combination with CNNs to improve model accuracy and generalization.