Faces GAN

For the final project of Udacity’s Deep Learning course I built a faces generator using a generative adversarial network. The gist of this approach is to build two competing neural networks, one to generate fake images and one to detect whether an image is fake or real. By training both networks in parallel we eventually end up with a generator network that produces images that look just like our dataset; and we discard the detector network. For this project we used the CelebA dataset of celebrity pictures so the network learned to generate celebrity creepy faces.