Other Resources =============== **Scikit-learn astronomy 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:** ``_ The scikit-learn documentation is extensive, and features detailed information on many of the routines used in the astroML examples. **Matplotlib documentation:** ``_ Matplotlib enables all the plots on this website, and its website includes extensive documentation and examples. See especially the example gallery. **IPython documentation:** ``_ 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 user. **Python scientific lecture notes:** ``_ 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 computing.