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Efficient Computing With NumPy - Jake Vanderplas

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Jake Vanderplas

Jake Vanderplas is an NSF post-doctoral fellow at University of Washington, working jointly between the Computer Science and Astronomy departments. His research involves applying recent advances in machine learning to large astronomical datasets, in order to learn about the Universe at the largest scales. He is co-author of "Statistics, Data Mining, and Machine Learning in Astronomy", a Python-centric textbook to be published by Princeton Press in 2013, and has presented many technical talks and papers in this subject area.

In the Python world, Jake is active in maintaining and contributing to several core Python scientific computing packages, including Scikit-learn, Scipy, Matplotlib, and others. He occasionally blogs on python-related topics at http://jakevdp.github.com.

What is PyData?
PyData.org is the home for all things related to the use of Python in data management and analysis. This site aims to make open source data science tools easily accessible by listing the links in one location. If you would like to submit a download link or any items to be listed in PyData News, please let us know at: [email protected]

Conferences
PyData conferences are a gathering of users and developers of data analysis tools in Python. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply the language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.

We aim to be an accessible, community-driven conference, with tutorials for novices, advanced topical workshops for practitioners, and opportunities for package developers and users to meet in person.

A major goal of PyData events and conferences is to provide a venue for users across all the various domains of data analysis to share their experiences and their techniques, as well as highlight the triumphs and potential pitfalls of using Python for certain kinds of problems.

PyData is organized by NumFOCUS with the generous help and support of our sponsors. Proceeds from PyData are donated to NumFOCUS and used for the continued development of the open-source tools used by data scientists If you would like to volunteer to be a part of the PyData team contact us at: [email protected]
Category
Computing
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