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Training MNIST benchmark with PyTorch

Xinyu Liu


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{
  "description": "This notebook reproduces a simple benchmark experiment that trains a convolutional neural network based on the MNIST dataset. In particular, the neural network is built and trained with PyTorch.\n\nMNIST is a database with 60,000 training images and 10,000 testing images that contains hand-written digits. Please see http://yann.lecun.com/exdb/mnist/ for more details.", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "@type": "Person", 
      "name": "Xinyu Liu"
    }
  ], 
  "headline": "Training MNIST benchmark with PyTorch", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2020-09-09", 
  "url": "https://zenodo.org/record/4344415", 
  "keywords": [], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.4344415", 
  "@id": "https://doi.org/10.5281/zenodo.4344415", 
  "@type": "ScholarlyArticle", 
  "name": "Training MNIST benchmark with PyTorch"
}
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