RichardScottOZ/Geoscience-Data-Quality-for-Machine-Learning
Python package for looking at the problems associated with geoscience datasets for data science
Geoscience Data Quality for Machine Learning helps geoscientists and exploration managers combine various geological, geophysical, and remote sensing datasets into reliable broad-scale machine learning models. It takes in disparate geoscience data, such as survey metadata or vector datasets, and quantifies and maps data quality, outputting quality scores and rasterized quality maps. This tool is for geoscience professionals who need to evaluate and prepare diverse spatial datasets for robust predictive modeling.
Use this if you are integrating varied geoscience datasets across large areas and need to understand and quantify their quality before using them in machine learning models.
Not ideal if your datasets are already harmonized, of known high quality, or if your primary focus is on small, localized studies rather than broad-scale analysis.
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Language
Jupyter Notebook
License
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Last pushed
Mar 10, 2026
Commits (30d)
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