Generative Adversarial Network architecture
Generative Adversarial Networks (GANs) are powerful neural networks used for unsupervised learning. They consist of a discriminator and a generator. Through adversarial training, GANs produce data nearly identical to real data. At Xonique, we leverage GANs where the generator creates new data, and the discriminator evaluates its authenticity until it can't distinguish between real and generated data.
More info- https://shorturl.at/xzPlh
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