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An introduction to GANs using the MNIST Handwritten Digit Dataset

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MNIST-Digit-Generation

Goal

This project implemented a Generative Adversarial Network (GAN) with MNIST data set. This project was completed in Python 3 using Keras.

Models

  • Fully-Connected, Feed-Forward Genreator and Discriminator - Showing Very Good results below
  • Convolutional Genreator and Discriminator - Untested, needs additional work

Results

The Feed-Forward model setup showed good results for generating MNIST digits. It is clear there is still some mode collapse, however I amd satisfied with the results of the Genreator.

The image below shows a sample of 100 random digits generated.

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An introduction to GANs using the MNIST Handwritten Digit Dataset

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