Building & Training GAN Model From Scratch In Python

Author(s): Youssef Hosni

Originally published on Towards AI.

Develop Your Own Generative Adversarial Networks with This Complete Python Tutorial

GANs are a powerful type of generative model that can synthesize new and realistic images. By walking through the complete implementation, readers will gain a solid understanding of how GANs work behind the scenes.

The tutorial begins by importing necessary libraries and loading the Fashion-MNIST dataset that will be used to train the GAN. Code samples are then presented to build the core components of a GAN — the generator and discriminator models.

Further sections explain how to construct a combined model that trains the generator to fool the discriminator, as well as how to design a training function that optimizes the… Read the full blog for free on Medium.

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Published via Towards AI