Repository files navigation

This is the source code fora 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
v0.2.0	2019-02-22

If you'd like to cite the evolving book, instead of a specific version, use the following DOI:https://doi.org/10.5281/zenodo.1412824. Here is the bibtex entry for the book:

@BOOK{BobraMason2019,       author = {{Bobra}, Monica G. and {Mason}, James P.},        title = "{Machine Learning, Statistics, and Data Mining for Heliophysics}",         year = "2019",          doi = {10.5281/zenodo.1412824},       adsurl = {https://ui.adsabs.harvard.edu/abs/2018mlsd.book.....B}}