In this repository I have the jupyter notebook and other files that I used for the lesson about deep convolutional generative adversarial network (DCGAN).
In this exercise we had to define both the generator and discriminator networks of a GAN that would read, ultimately, be able to generate images of numbers as close as possible to real pictures.
I utilized an Adam optimizer for both the generator and discriminator networks, as described in the paper of the creator of DCGANs: https://arxiv.org/pdf/1511.06434.pdf