12. Other Resources
- Scikit-learn astronomy tutorial: http://astroML.github.com/sklearn_tutorial
- This is an online tutorial which introduces the scikit-learn interface and
the fundamental ideas of machine learning, and applies them within the
context of astronomical data analysis. It includes several videos of the
tutorial being presented at conferences.
- Scikit-learn documentation: http://scikit-learn.org
- The scikit-learn documentation is extensive, and features detailed
information on many of the routines used in the astroML examples.
- Matplotlib documentation: http://matplotlib.org
- Matplotlib enables all the plots on this website, and its website includes
extensive documentation and examples. See especially the example gallery.
- IPython documentation: http://ipython.org
- IPython is is an enhanced interactive python interpreter, and also
provides a framework for parallel computing and cross-platform sharing
of code and results. It is an essential tool for any scientific
- Python scientific lecture notes: http://scipy-lectures.github.com/
- These notes cover some of the basics of scientific python, including
numpy, scipy, and matplotlib. From there they move into an in-depth
exploration of more advanced and specialized topics in scientific