[DOC] Implement an example using a neural-net based classifier to do Classifier CI Testing

[adam2392]

We are interested in a new user contribution of an example where they demonstrate how to use the ClassifierCITest with a scikit-learn classifier and a neural-net based classifier.

This would enable CI testing over high-dimensional objects, such as images and pixels for example. The example does not necessarily need to operate over images/pixels.

Ideally the pytorch model is already trained and fitted, and the model is just pulled from something like hugging face. We can introduce a test-time dependency on pytorch and hugging face. Then the model should be relatively small, so it can run in the continuous integration platform.

"Could we expand this method to work with a neural-net based classifier using Keras or Pytorch? It likely feels like overkill but it would be a first step to telling a story to the broader community that this repo is using cutting edge "deep" methods. We could also workshop an example with multidimensional variables later (e.g. pixels) though not in this PR.

Originally posted by @robertness in #28 (review)"