Fashion training set consist of 70,000 images divided into 60,000 training and 10,000 testing samples. Dataset samples consists of 28x28 grayscale image associated with a label from 10 calsses.
The Fashion-MNIST clothing classification problem is a new standard dataset used in computer vision and deep learning.
Although the dataset is relatively simple, it can be used as the basis for learning and practicing how to develop, evaluate, and use Forward propagation for image classification from scratch.
Each Image is 28 pixel in hight and 28 pixel in width, for a total of 784 pixels in total. Each pixel has a single Pixel value associated with it, indicating the lightness or darkness of the pixel.