Building our first simple GAN

In this video we build a simple generative adversarial network based on fully connected layers and train it on the MNIST dataset. It’s far from perfect, but it’s a start and will lead us to implement more advanced and better architectures in upcoming videos. I learned a lot and was inspired to make these GAN videos by the GAN specialization on coursera. Below you’ll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link. affiliate: non-affiliate: GitHub Repository: ✅ Equipment I use and recommend: ❤️ Become a Channel Member: ✅ One-Time Donations: Paypal: Ethereum: 0xc84008f43d2E0bC01d925CC35915CdE92c2e99dc ▶️ You Can Connect with me on: Twitter - LinkedIn - GitHub - GAN Playlist: PyTorch Playlist: OUTLINE: 0:00 - Introduction 0:29 - Building Discriminator 2:14 - Building Generator 4:36 - Hyperparameters, initializations, and preprocessing 10:14 - Setup training of GANs 22:09 - Training and evaluation