- Overview of AstroML from/for a non-expert
- Adele Plunkett
- Abstract
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Straight from the AstroML webpage (www.astroml.org): "AstroML is a Python module for machine
learning and data mining," with a goal to implement "common tools and routines used for
statistical data analysis in astronomy and astrophysics." It makes clever use of Python
routines you may already use, including numpy, scipy, scikit-learn, matplotlib, and others.
Entire courses can be formulated around the more advanced statistical topics that AstroML can
handle. On the other hand, even a python beginner can find AstroML a user-friendly tool for
advanced statistical analyses in astronomy. The goal of this presentation is to (broadly)
summarize the AstroML python module and the related resources: including the webpage, github
repository and the related text book "Statistics, Data Mining, and Machine Learning in Astronomy"
(Ivezic, Connolly, VanderPlas & Gray 2014). While I am neither an expert in Python nor in machine
learning/data mining, I find AstroML helpful to know where to turn when faced with a tricky
statistical problem, or a nice-looking plot.
- Repository
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- iPython notebook.
- YouTube course for reference (tip by J. Milli).
- Intro to scikit-learn (tip by A. Mérand).
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