astroML is a Python module for machine learning and data mining that accompanies the book "Statistics, Data Mining, and Machine Learning in Astronomy", by Željko Ivezić, Andrew Connolly, Jacob Vanderplas, and Alex Gray. astroML is built on numpy, scipy, scikit-learn, matplotlib, and astropy, and contains a growing library of statistical and machine learning routines for analyzing astronomical data.
In this interactive book we provide notebooks that describe the statistical and machine learning methods used in astroML together with code that runs these methods on existing astronomical data sets. The structure of this interactive book follows the chapters of "Statistics, Data Mining, and Machine Learning in Astronomy". Each notebook can viewed through the browser (with navigation links at the side of the page), be downloaded to your own computer, or be executed directly using Binder or Google Colab
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chapter1/README
chapter2/README
chapter3/README
chapter4/README
chapter5/README
chapter6/README
chapter7/README
chapter8/README
chapter9/README
chapter10/README
For contributing guidelines, please follow the documentation in the astroML-notebooks github repository.