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Uncertainty quantification fo ML - collection of scripts, tutorials and templates

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Uncertainty Quantification

List of templates focused on uncertainty quantification applied to machine learning and deep learning


Topics

  • Difference between prediction and confidence intervals
  • Quantile regression
  • Uncertainty quantification applied to ANNs
  • How to estimate your model uncertainty with frameworks such as KERAS, PyTorch, XGBoost, LightGBM and ScikitLearn

A note on the notebook rendering

Each notebook has two versions (all python scripts are unaffected by this):

  • One where all the markdown comments are rendered in black& white. These are placed in the folder named GitHub_MD_rendering where MD stands for MarkDown.
  • One where all the markdown comments are rendered in coloured.

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