Building Our First Simple GAN

Learn to build a simple generative adversarial network (GAN) using fully connected layers and train it on the MNIST dataset in this 24-minute video tutorial. Explore the process of constructing both the discriminator and generator components, setting up hyperparameters, initializations, and data preprocessing. Dive into the setup for training GANs, and conclude with hands-on training and evaluation of the model. While the resulting GAN may not be perfect, this tutorial serves as a foundational starting point for implementing more advanced and effective architectures in future lessons.