Many examples of deep learning algorithms in either research papers, blog posts or books deal with the MNIST dataset. We should not be the exception and introduce a small use case for autoencoders using MNIST.
The motivation is the following, suppose you want to detect fake banknotes automatically. Then you would need to teach the computer what the representation of the average banknote is to be able to detect those that have significant differences. Due to the large volume of cash transactions happening every day worldwide, and to the increasing sophistication of fraudsters, it would be unthinkable to do this process manually. One way to do this is to use sophisticated imaging software, which is how counterfeit ...
