Machine Learning in Linux: astroML – statistical data analysis in astronomy and astrophysics
In essence, Machine Learning is the practice of using algorithms to parse data, learn insights from that data, and then make a determination or prediction. The machine is ‘trained’ using huge amounts of data.
In other words, Machine Learning is about building programs with tunable parameters (typically an array of floating point values) that are adjusted automatically so as to improve their behavior by adapting to previously seen data.
astroML is a Python module for machine learning and data mining built on NumPy, SciPy, scikit-learn, matplotlib, and Astropy.
The aim of the project is to offer a repository of Python implementations of common tools and routines used for statistical data analysis in astronomy and astrophysics, and to provide a uniform and easy-to-use interface to freely available astronomical datasets.