This project implements a Convolutional Neural Network (CNN) to classify images of cats and dogs. The model takes an input image, applies convolutional and pooling layers to automatically extract spatial features such as edges, textures, and shapes, and then uses fully connected layers to predict whether the image belongs to a cat or a dog class. It highlights practical experience with CNNs for image classification and working with real-world visual data.