Zalando Research’s image-classification dataset contains small grayscale pictures of fashion products across ten classes, with separate training and test sets. It was designed as a more challenging drop-in alternative to handwritten-digit MNIST while retaining a familiar structure. Useful for machine-learning lessons, quick model comparisons and testing an image-classification pipeline before moving to larger or more complex data.