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Alex Lin
376 followers -
a data geek with the wildest dreams
a data geek with the wildest dreams

376 followers
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Help Michael Nielsen make it with this interesting book project, (indiegogo campaign).

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Simple real-time large-scale machine learning infrastructure. https://github.com/cloudera/oryx

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I am in Washington today to announce a large initiative involving NYU, the University of Washington and UC Berkeley.
The 5 year initiative is funded by a $37.8M grant from the Sloan Foundation and the Moore Foundation.

I am the lead faculty for NYU. My counterpart at UW is +Ed Lazowska and at Berkeley +Saul Perlmutter.

The initiative is called the Moore/Sloan Data Science Environments. It seeks to jump-start 'data-intensive science and discovery'.

And we are hiring: faculty, data science postdoctoral fellows, and data science tool builders.

NYTimes: Program Seeks to Nurture ‘Data Science Culture’ at Universities
http://nyti.ms/1ckszfM

Update: article at the Huffington Post: http://www.huffingtonpost.com/vicki-chandler/a-bold-experiment-to-tack_b_4255809.html

Moore Foundation press release: http://www.moore.org/programs/science/data-driven-discovery/data-science-environments

Sloan Foundation press release: http://www.sloan.org/fileadmin/media/files/press_releases/datascience.pdf



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Awesome (plain english) explanation of Fourier transforms: http://bit.ly/1b8k7SA - aka, the magic behind audio compression, plus a very large number of other applications.
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Enjoying the Applied Predictive Modeling book by Max Kuhn and Kjell Johnson as well as their caret R package.

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MOA is an open source framework for data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection and recommender systems) and tools for evaluation. Related to the WEKA project, MOA is also written in Java, while scaling to more demanding problems http://moa.cms.waikato.ac.nz/
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