GAD Academy Students Experiments in GAN

 

 

The GAD Academy’s current team of students is working on Generative Adversarial Networks. 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 to generate or output new examples that plausibly could have been drawn from the original dataset. The GAD Academy students focused on image data sets based on nature, art and urbanism led by GAD Academy tutor Kemal Arda Alkin.

GAN(Generative Adversial Networks) VIDEO; https://www.instagram.com/p/CNu0badhl_n/?utm_source=ig_web_copy_link

 

 

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