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ENH added AWeber's testimonial
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doc/testimonials/testimonials.rst

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@@ -85,7 +85,7 @@ Mark Ayzenshtat, VP, Augmented Intelligence
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</span>
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`Télécom ParisTech <http://www.telecom-paristech.fr>`_
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`AWeber <http://aweber.com/>`_
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------------------------------------------
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.. raw:: html
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<div class="logo">
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.. image:: images/aweber.png
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:target: http://aweber.com/
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</div>
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The scikit-learn toolkit is indispensable for the Data Analysis and Management
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team at AWeber. It allows us to do AWesome stuff we would not otherwise have
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the time or resources to accomplish. The documentation is excellent, allowing
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new engineers to quickly evaluate and apply many different algorithms to our
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data. The text feature extraction utilities are useful when working with the
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large volume of email content we have at AWeber. The RandomizedPCA
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implementation, along with Pipelining and FeatureUnions, allows us to develop
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complex machine learning algorithms efficiently and reliably.
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Anyone interested in learning more about how AWeber deploys scikit-learn in a
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production environment should check out talks from PyData Boston by AWeber's
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Michael Becker available at https://github.com/mdbecker/pydata_2013
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<span class="testimonial-author">
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Michael Becker, Software Engineer, Data Analysis and Management Ninjas
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</span>
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