Fake Handwritten Digits
In this project, we will train a model that will eventually learn to write handwritten digits.
INPUT: we will use torchvision dataset that is built-in in PyTorch
OUTPUT: generated data
- GAN (Generative Adversarial Networks)
- Leaky ReLU Activation Function
We used PyTorch built-in torchvision module as a data source which called MNIST handwritten digit. We implemented a GAN (Generative Adversarial Networks) model that implemented the Leaky ReLU activation function. We trained the Discriminator and Generator Neural Networks. The purpose of the Generator is to create fake images and the Discriminator to identify between the fake and real images. They worked together to finally generate some very realistic fake images which are hard to differentiate.