The classification of images into cats and dogs is a classic binary classification problem in the field of computer vision. This problem is often used as a benchmark for testing the performance of image classification algorithms, particularly Convolutional Neural Networks (CNNs).
In the cats and dogs problem, we are given a dataset of images, each of which is labeled as either a cat or a dog. The goal is to train a CNN that can accurately classify new, unseen images as either a cat or a dog.