Data Science, Machine Learning, Deep Learning, Artificial Intelligence, Computer Vision.
samples. These fake samples are then passed to the discriminator for evaluation. The generator aims to generate fake samples that are indistinguishable from real samples, fooling the discriminator into classifying them as real. The generator’s weights are updated based on the feedback from the