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MNIST Dataset

Overview

  • Training Set: 60,000 training images & labels
  • Test Set: 10,000 test images & labels
  • Handwritten single digits ranging 0-9

Data Format

  • Each 28 x 28 pixel single digit image is represented as a 28 x 28 array, with grayscale (single color channel) values ranging from 0 (white) to 255 (black).
    • It can be normalized to a range of 0-1.
  • With 60,000 images, each with a single channel sized 28 x 28 x 1 results in a 4D array:
    • (60,000, 28, 28, 1)
    • The '1' denotes a single color channel: grayscale. Color images would have a value of '3'.
  • When the 28 x 28 array is flattened it is a 1D vector measuring 784 units. Note that the flattening of this array removes the information about the pixel relationships with adjacent pixels, but this can otherwise be accounted for in a CNN. This results in an overall training tensor of a 784 x 60,000 array.
  • Labels
    • Labels are one-hot encoded into a single array for each image and identified by the index position in the array.
      • Example label for a digit of 4: [0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
    • With labels identifying 1 of the 10 available values, the training labels are a (60,000, 10) 2D array.

Sample Image

The following is a sample of the data for a single image depicting a handwritten number '5'.

Documentation

TensorFlow

TF MNIST Dataset

Distributed Training with MNIST Dataset

Documentation