Representing images and outputs

This section mainly focuses on how images are represented on a computer and how to feed this to the neural network. Based on what we've learned so far, neural networks predict only binary classes, where the answer is yes or no, or right or wrong. Consider the example of predicting whether a patient would have heart disease or not. The answer to this is binary in nature—yes or no. We will now learn to train our neural network to predict multiple classes using softmax.

A computer perceives an image as a two-dimensional matrix of numbers. Look at the following diagram:

These numbers make little sense to us, but ...

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