mllam/mllam-data-prep
generation of training-optimised weather datasets from declarative syntax
This tool helps meteorologists and climate scientists prepare complex weather datasets for machine learning models. You provide a YAML configuration file describing your raw weather data sources and the specific variables, transformations, and output structure needed. It then generates a tailored, training-optimized weather dataset, ready for model input. This is designed for researchers building data-driven weather forecasting systems.
Use this if you need to create custom, machine learning-ready weather datasets from various raw meteorological sources with specific variable extractions and transformations.
Not ideal if you're not working with weather or climate data, or if you only need simple data cleaning without complex remapping for machine learning models.
Stars
15
Forks
29
Language
Python
License
—
Category
Last pushed
Feb 28, 2026
Commits (30d)
0
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