High Resolution Generative Adversarial Networks

Create a GAN capable of generating high resolution images using TensorFlow 2.0 · Distribute training on a TPU or multiple GPUS · Implement the R2 This course covers the fundamentals necessary for a state-of-the-art GAN. Anyone who experimented with GANs on their own knows that it's easy to throw together a GAN that spits out MNIST digits, but it's another level of difficulty entirely to produce photorealistic images at a resolution higher than a thumbnail. You'll create and train a GAN that can be used in real-world applications. And because training high-resolution networks of any kind is computationally expensively, you'll also learn how to distribute your training across multiple GPUs or TPUs. This allows students to train generators up to 512x512 resolution with no hardware costs at all.