In this video we take a look at a way of also deciding what the output from the GAN should be. Specifically the output is conditioned on the labels that we send in and as an example we take a look at training on MNIST (of course) ;) But these ideas extend to any dataset you’re working with really!

OUTLINE:
0:00 - Introduction
0:56 - Modifying Generator and Discriminator
6:58 - Modifying Gradient Penalty
7:35 - Modifying Training
10:43 - Evaluation & Ending

Github Repository: https://github.com/aladdinpersson/Machine-Learning-Collection

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#pytorch #gan