Skill

Generative Adversarial Networks (GANs)

Data Science, Analytics and AI/ML

Generative Adversarial Networks (GANs) are a class of machine learning models, introduced by Ian Goodfellow in 2014, in which a generator network and a discriminator network are trained simultaneously in an adversarial process to produce increasingly realistic synthetic data. They have been widely used to generate photorealistic images, enhance image resolution, and create synthetic training data. AI researchers and engineers apply GANs across computer vision, art generation, and data augmentation tasks.

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