MNIST is a classic dataset of small images of handwritten digits, 0 to 9, used to train and test image classifiers.
In plain words
Each MNIST example is a tiny 28 by 28 pixel grayscale picture of one handwritten digit, paired with a label saying which digit it is. There are 60,000 pictures for training and a separate 10,000 for testing. Libraries such as Keras and TensorFlow Datasets can load it directly, which makes it easy to try out image classification.
A quick example
A typical first project: load MNIST with one line of library code, train a small neural network on the 60,000 training images, then measure how many of the 10,000 test digits it labels correctly.
Where you'll meet it
- Tutorials and courses on image classification.
- Quick sanity checks for new training code.
Related
Sources
- DocsMNIST digits classification dataset, Keras documentation · read 29 Sept 2026
- Docsmnist, TensorFlow Datasets catalog · read 18 Oct 2026
Checked by WhatIsAI against the sources above · 18 Oct 2026. Spotted an error? Report it.