Summary
In this chapter, we have explored a whole new kind of quantum machine learning models: quantum GANs. Unlike the models we had considered before, these are used primarily for generation tasks. And, unlike our previous models, they are trained in a fully unsupervised manner.
After understanding what GANs are in general, we introduced the general notion of a QGAN, and then we learned how to implement a couple of QGAN models using PennyLane and Qiskit.
With this, we also conclude our study of quantum machine learning for this book. We hope that you have had a good time learning about all these ways of making quantum computers learn! But your quantum journey does not need to end here. Please, keep on reading for a sneak peek of what you can expect in the near future in the quantum computing field.
