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GANs in Action

9 Books on Generative Adversarial Networks (GANs)

Generative Adversarial Networks, or GANs for short, were first described in the 2014 paper by Ian Goodfellow, et al. titled “Generative Adversarial Networks.” Since then, GANs have seen a lot of attention given that they are perhaps one of the most effective techniques for generating large, high-quality synthetic images. As such, a number of books […]

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Generative Adversarial Networks with Python

Generative Adversarial Networks with Python

Generative Adversarial Networks with Python Deep Learning Generative Models for Image Synthesis and Image Translation …so, What are Generative Adversarial Networks? Generative Adversarial Networks, or GANs, are a deep-learning-based generative model. More generally, GANs are a model architecture for training a generative model, and it is most common to use deep learning models in this […]

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A Gentle Introduction to General Adversarial Networks (GANs)

A Gentle Introduction to Generative Adversarial Networks (GANs)

Generative Adversarial Networks, or GANs for short, are an approach to generative modeling using deep learning methods, such as convolutional neural networks. Generative modeling is an unsupervised learning task in machine learning that involves automatically discovering and learning the regularities or patterns in input data in such a way that the model can be used […]

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Example of Photorealistic Human Faces Generated by a GAN

Best Resources for Getting Started With GANs

Generative Adversarial Networks, or GANs, are a type of deep learning technique for generative modeling. GANs are the techniques behind the startlingly photorealistic generation of human faces, as well as impressive image translation tasks such as photo colorization, face de-aging, super-resolution, and more. It can be very challenging to get started with GANs. This is […]

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