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    Jupyter Notebook
  • Created over 2 years ago
  • Updated about 2 years ago

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Repository Details

The project evaluates causal effects in the prediction of mud loss during drilling activities. Model agnostic metrics, PFI and Shapley, are used to analyse each feature to understand their global implications in predicting mud loss. Several supervised machine learning models are used to predict the mud loss using these selected features.