This repository contains a GAN model that generates numbers between 0 to 9 using the MNIST dataset.
The GAN model consists of two neural networks: a generator and a discriminator, which compete against each other to improve their performance. The generator creates images of handwritten digits, and the discriminator evaluates their authenticity.
- Dataset: MNIST
- Framework: TensorFlow/Keras
- Epochs: 25000
The model successfully learned to generate realistic digits after training for 25000 epochs.
Watch the progression of learning over epochs in the video.