Here, the focus is on building a GAN framework to learn a 1D function which is a quadratic function here but can be modified. This is based on an assignment from the course 'Introduction to Machine Learning' at the University of Toronto.
Generative Adversarial Networks come under Unsupervised Machine Learning techniques but, unlike methods like clustering, GANs work by employing Neural Networks which is essentially a part of the Supervised Machine Learning facet. Read more here: https://poloclub.github.io/ganlab/
Example plots:
