MNIST

MNIST (Modified National Institute of Standards and Technology) is a large collection of handwritten digit images used for training and testing machine learning models. It contains 70,000 grayscale pictures of digits from 0 to 9, each standardized in size. Researchers use MNIST to teach computers how to recognize and classify handwritten numbers, a foundational task in machine learning. Its well-organized dataset makes it a popular benchmark for developing and comparing image recognition algorithms, helping advance technologies like optical character recognition and digital handwriting analysis.