I would start with these two links. If you understand python syntax then you're most of the way there. The first link basically just describes the concepts behind adversarial networks, and the second actually has code that should run fine on a 2070 if you want to use that as a springboard. If you run into hardware limitations, Google Colab is basically a free python notebook that will do all the gpu processing on their machines, with some limitations that can be removed for $10 a month (how long your sessions can last etc). The code on that page should run fine on the free tier though. Otherwise, just youtube GANs and watch talks and stuff. The computerphile video is a good place to start for someone who already knows a bit of math and programming. https://www.youtube.com/watch?v=Sw9r8CL98N0
https://machinelearningmastery.com/what-are-generative-adversarial-networks-gans/ https://machinelearningmastery.com/how-to-develop-a-generative-adversarial-network-for-a-cifar-10-small-object-photographs-from-scratch/
I would start with these two links. If you understand python syntax then you're most of the way there. The first link basically just describes the concepts behind adversarial networks, and the second actually has code that should run fine on a 2070 if you want to use that as a springboard. If you run into hardware limitations, Google Colab is basically a free python notebook that will do all the gpu processing on their machines, with some limitations that can be removed for $10 a month (how long your sessions can last etc). The code on that page should run fine on the free tier though. Otherwise, just youtube GANs and watch talks and stuff. The computerphile video is a good place to start for someone who already knows a bit of math and programming. https://www.youtube.com/watch?v=Sw9r8CL98N0