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Let us build a simple Generative Adversarial Network (GAN) from scratch | GAN theory and intuition
Imagine you have Neural Network (NN1) whose job is to initially output a random noise 32x32 matrix (a noise image). Now imagine there is a second neural network (NN2). The output of NN1 is given as the input to NN2. NN2 is trained to predict a probability (p) for the input 32x32 image to be the very specific image of a ‘cat’. Since the ...
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