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ML notes

Contents

  1. PyTorch demo: image classification
  2. Experimenting with simple random sampling versus stratified sampling
  3. Using pytorch as an optimizer for distribution fitting
  4. Classifying distributions using deep learning

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Notes on machine learning

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