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This is the source code for a book about machine learning, statistics, and data mining for heliophysics.

This book includes a collection of interactive Jupyter notebooks, written in Python, that explicitly shows the reader how to use machine learning, statistics, and data minining techniques on various kinds of heliophysics data sets to reproduce published results.

The contents of this book are licensed for free consumption under the following license:
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)


We publish each release of HelioML on Zenodo; here is a list of every version:

Version Date DOI
v0.1.0 2018-09-10 10.5281/zenodo.1412825
v0.2.0 2019-02-22 10.5281/zenodo.2575738
v0.3.0 2020-05-11 10.5281/zenodo.3820932
v0.4.0 2021-02-08 10.5281/zenodo.4521380

If you'd like to cite the evolving book, instead of a specific version, use the following DOI: Here is the bibtex entry for the book:

       author = {{Bobra}, Monica G. and {Mason}, James P.},
        title = "{Machine Learning, Statistics, and Data Mining for Heliophysics}",
         year = "2020",
          doi = {10.5281/zenodo.1412824},
       adsurl = {}