GANs-in-Action/gans-in-action
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
This project provides practical, hands-on examples for anyone learning about Generative Adversarial Networks (GANs). It helps you understand how different GAN architectures work by letting you run and experiment with real code. You put in data like images or labels, and the system generates new, similar data, which is useful for researchers and students in machine learning.
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Use this if you are studying Generative Adversarial Networks and want to implement and understand various GAN architectures like DCGAN, CycleGAN, or Progressive GAN through concrete code examples.
Not ideal if you are a non-technical user looking for a ready-to-use application to generate images or perform data augmentation without delving into the underlying code.
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Jul 23, 2025
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