Introduction

The first network which is the generator (G) learns the real input data and generates the corresponding data while another model is a discriminator(D) which has a check on the authenticity whether the generated data belongs to the training dataset. The generative model neural network takes an input noise vector(z) which is then sampled through ... ................
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