Summary

We have seen in this chapter how PyTorch Lightning can be used to create semi-supervised learning models easily with a lot of out-of-the-box capabilities. We have seen an example of how to use machines to generate the captions for images as if they were written by humans. We have also seen an implementation of code for an advanced neural network architecture that combines the CNN and RNN architectures.

Creating art using machine learning algorithms opens new possibilities for what can be done in this field. What we have done in this project is a modest wrapper around recently developed algorithms in this field, extending them to different areas. One challenge in generated text that often comes up is a contextual accuracy parameter, which measures the accuracy of created lyrics based on the question, does it make sense to humans? The proposal of some sort of technical criterion to be used to measure the accuracy of such models in this regard is a very important area of research...