We're going to build a GAN to generate some images using Tensorflow. This will help you grasp the architecture and intuition behind adversarial approaches to machine learning. We're building a Deep Convolutional GAN to generate MNIST digits.
Code for this video:
https://github.com/llSourcell/Generative_Adversarial_networks_LIVE/blob/master/EZGAN.ipynb
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More Learning resources:
http://guimperarnau.com/blog/2017/03/Fantastic-GANs-and-where-to-find-them
http://www.cs.toronto.edu/~dtarlow/pos14/talks/goodfellow.pdf
https://datawarrior.wordpress.com/2017/02/03/generative-adversarial-networks/
https://www.quora.com/What-are-Generative-Adversarial-Networks
http://nuit-blanche.blogspot.com/2017/01/nips-2016-tutorial-generative.html
http://www.paddlepaddle.org/develop/doc/tutorials/gan/index_en.html
http://gkalliatakis.com/blog/delving-deep-into-gans
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