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Generating Artificial Faces with Machine Learning

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In today’s article, we are going to generate realistic looking faces with Machine Learning. In order to do so, we are going to leverage Generative Adversarial Networks ( GANs ), and more specifically Deep Convolutional Generative Adversarial Networks ( DCGANs ). By the end of this post, you will be able to successfully train a GAN to sample an infinite amount of images based on a given dataset, which in our case will be human faces. Let’s start with a simple question. Can you tell which of the following images are real and which ones are fake? Do they exist? We will get back to this later, stay tuned! Meanwhile, let’s proceed with GANs and try to artificially create realistic looking faces. Deep Convolutional Generative Adversarial Networks (DCGANs) If you are completely new to the GANs field, I recommend you to check my previous article that covers its absolute basics. Even if you are not a beginner, I still recommend you to take a loo...
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