Open Source Projects
AstroML is a Python module for machine learning and data mining in Astronomy and Astrophysics. It contains many commonly-used tools from the astronomical literature, and hundreds of examples of their use. I wrote this package to accompany our textbook, Statistics, Data Mining, and Machine Learning in Astronomy.
Scikit-Learn is a powerful and extensive machine learning library written in Python. I have contributed in many areas of the project, but primarily in the area of generalized N-point problems & manifold learning.
mpld3 is a project which leverages D3js to produce interactive browser-based visualizations from matplotlib figures. Though interactive, the resulting figures are not tied to the Python kernel, so they can be used statically on web pages and blogs. To see mpld3 in action, take a look at my initial blog post, or see some examples here and here.
SciDB-Py is a set of python wrappers for the SciDB project which provides a natural, numpy-like interface to large-scale array-based computations. The project is a collaboration between myself and the folks at Paradigm4.
Scipy is a collection of Python tools for scientific computing. My main contributions have been in the sparse matrix toolkit, primarily in iterative sparse matrix decompositions and fast graph algorithms.
I also have made numerous small contributions to projects such as NumPy, Matplotlib, IPython, Hyde, Pelican, and others, and have open-sourced much of my other code and teaching materials. See my GitHub profile for details.