DataDrivenGalaxyEvolution/galevo23-tutorials
Tutorials for the KITP Galevo23 program
These tutorials help astronomers and researchers explore how galaxies evolve by using modern data analysis and machine learning techniques. You'll work through practical examples using astronomical data and simulations, learning to apply methods like neural networks to understand galaxy formation. The materials are designed for astrophysicists and other scientific researchers interested in applying computational methods to complex astronomical datasets.
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Use this if you are an astrophysicist or data scientist in astronomy looking to learn or apply machine learning methods to galaxy evolution studies, from analyzing simulation outputs to modeling observational data.
Not ideal if you are looking for a general introduction to machine learning without a specific focus on astrophysical applications or if your primary interest is not galaxy evolution.
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Jupyter Notebook
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GPL-3.0
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Last pushed
Aug 17, 2023
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