ai2es/WAF_ML_Tutorial_Part2
Python code to assist in familiarizing meteorologists with machine learning
This project helps operational meteorologists understand and apply neural networks to forecasting. Using a smaller, more accessible version of the Storm EVent ImagRy (SEVIR) dataset, it guides users through practical examples. The output is a better grasp of how to use deep learning for weather prediction and analysis, enabling meteorologists to incorporate these advanced techniques into their work.
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Use this if you are a meteorologist curious about incorporating neural networks into your weather forecasting and analysis workflows.
Not ideal if you are looking for a plug-and-play solution for immediate operational use or if you are not interested in learning the underlying machine learning concepts.
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Language
Jupyter Notebook
License
CC0-1.0
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Last pushed
Dec 31, 2024
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