Python Codebase and Jupyter Notebooks - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Description

Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, and distribute with attribution. Full license details are included within the archive. See "documentation.zip" for setup instructions and file trees annotated with module descriptions.

Resources

Name Format Description Link
57 Project-specific output models. For additional information, see "annotated_file_tree_Results.txt" within documentation. https://gdr.openei.org/files/1402/PFA_ML_Sandbox_Results.zip
57 Annotated file trees, module descriptions, setup instructions, and license. https://gdr.openei.org/files/1402/documentation.zip
57 Project-specific input data formatted for use in Python modules ("Essentials"). For additional information, see "annotated_file_tree_Data.txt" within documentation. https://gdr.openei.org/files/1402/PFA_ML_Sandbox_Data.zip
57 Python modules and Jupyter Notebooks. For additional information, see "annotated_file_tree_Essentials.txt" within documentation. https://gdr.openei.org/files/1402/PFA_ML_Sandbox_Essentials.zip

Tags

  • nmfk
  • data
  • results
  • jupyter
  • great-basin
  • principal-component-analysis
  • non-negative-matrix-factorization
  • ann
  • python
  • pytorch
  • pfa
  • code
  • pca
  • model
  • git
  • script
  • artificial-neural-network
  • documentation
  • exploration
  • pandas
  • bayesian-neural-network
  • charaterization
  • geotiff
  • jupyter-notebook
  • algorithm
  • machine-learning
  • nevada
  • geothermal
  • bnn
  • energy

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Categories