Iterations are the number of steps through batches of the training data needed to complete one epoch.

For better understanding, consider the following example:

  • The total training set of images = 5000
  • Batch Size = 64

From the above values, 64 samples will be taken each time through the neural network forward and backward. This constitutes one iteration.

Therefore, if you are loading 64 images at a time (in one batch), to go through all 5000 images, you will need 5000 / 64 = about 78 iterations.

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