Training a Pytorch Lightning MNIST GAN on Google Colab

Marton Trencseni - Sat 20 February 2021 • Tagged with python, pytorch, gan, mnist, google-colab

I explore MNIST digits generated by a Generative Adversarial Network trained on Google Colab using Pytorch Lightning.

Softmax GAN after 5 epoch, 100 samples.

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MNIST pixel attacks with Pytorch

Marton Trencseni - Sat 01 June 2019 • Tagged with python, pytorch, cnn, torchvision, mnist, skl

It’s easy to build a CNN that does well on MNIST digit classification. How easy is it to break it, to distort the images and cause the model to misclassify?

MNIST attack accuracy

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Solving MNIST with Pytorch and SKL

Marton Trencseni - Thu 02 May 2019 • Tagged with python, pytorch, cnn, torchvision, mnist, skl

MNIST is a classic image recognition problem, specifically digit recognition. It contains 70,000 28x28 pixel grayscale images of hand-written, labeled images, 60,000 for training and 10,000 for testing. Convolutional Neural Networks (CNN) do really well on MNIST, achieving 99%+ accuracy. The Pytorch distribution includes a 4-layer CNN for solving MNIST. Here I will unpack and go through this example. We use torchvision to avoid downloading and data wrangling the datasets. Finally, instead of calculating performance metrics of the model by hand, I will extract results in a format so we can use SciKit-Learn's rich library of metrics.

MNIST example digits

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