Generative adversarial networks

Generative Adversarial Network (GAN)

A Generative Adversarial Network (GAN) is a type of machine learning model that is composed of two parts: a generator and a discriminator. The generator model generates fake data, such as fake images, while the discriminator model attempts to classify the fake data as real or fake. The generator and discriminator models are trained together …

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Generative adversarial networks

“Generative adversarial networks (GANs) are an exciting recent innovation in machine learning. GANs are generative models: they create new data instances that resemble your training data. For example, GANs can create images that look like photographs of human faces, even though the faces don’t belong to any real person. “ Now Train The Model Results