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

Please Subscribe! And like. And comment. That's what keeps me going.

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

Join us in the Wizards Slack channel: http://wizards.herokuapp.com/

And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/