CristianCosci/Generative_Adversarial_Networks_GAN__Overview
A small overview of what GANs and their main variants are, with related implementations.
This project provides an introduction to Generative Adversarial Networks (GANs), a type of neural network that can create new images. It explains how GANs take random noise as input and produce realistic-looking images as output, by having two networks (a generator and a discriminator) compete against each other. It's designed for machine learning practitioners and researchers who want to understand how GANs work and explore their common variations.
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Use this if you are a machine learning practitioner interested in generating realistic data, like images, and want to understand the foundational concepts and variations of Generative Adversarial Networks.
Not ideal if you are looking for a plug-and-play solution for immediate data generation without delving into the underlying machine learning models.
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Mar 28, 2023
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