May 2019
Intermediate to advanced
272 pages
7h 19m
English
Content preview from Hands-On Generative Adversarial Networks with Keras
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Experimental setup
In this section, we will start by implementing methods that are necessary for preparing and loading our data during training. Next, we will learn to implement auxiliary functions that are required for the Wasserstein GAN with Gradient Penalty. Last, we are going to write code to set up training and the training loop itself.
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