<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>reproducibility on DataScience.LA</title><link>https://datasciencela.github.io/tag/reproducibility/</link><description>Recent content in reproducibility on DataScience.LA</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>DataScience.LA, 2014–2021 · Read-only archive: comments are closed.</copyright><lastBuildDate>Wed, 29 Oct 2014 09:16:23 -0700</lastBuildDate><atom:link href="https://datasciencela.github.io/tag/reproducibility/index.xml" rel="self" type="application/rss+xml"/><item><title>LA R Meetup - November 11: Highlights from the useR! 2014 conference - Part 2</title><link>https://datasciencela.github.io/la-r-meetup-november-11-highlights-from-the-user-2014-conference-part-2/</link><pubDate>Wed, 29 Oct 2014 09:16:21 -0700</pubDate><guid>https://datasciencela.github.io/la-r-meetup-november-11-highlights-from-the-user-2014-conference-part-2/</guid><description>&lt;p&gt;At this meetup, five more LA R meetup members will present short talks of what they have learned at useR! 2014. This is the 2nd round of talks about useR! since we had twice as many volunteers to speak as we could accommodate in one meetup (indeed, useR! was that awesome). The first round of talks at our September meetup is &lt;a href="https://datasciencela.github.io/la-r-meetup-summary-highlights-from-the-user-2014-conference/"&gt;summarized here (with slides)&lt;/a&gt;.&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/la-r-meetup-november-11-highlights-from-the-user-2014-conference-part-2/feature.jpg"/></item><item><title>Python Data Science Meetup: Data Science with Python</title><link>https://datasciencela.github.io/python-data-science-meetup-data-science-with-python/</link><pubDate>Wed, 08 Oct 2014 09:37:41 -0700</pubDate><guid>https://datasciencela.github.io/python-data-science-meetup-data-science-with-python/</guid><description>&lt;p&gt;I&amp;rsquo;m pleased to announce the first event of our &lt;a href="https://datasciencela.github.io/announcing-the-new-pydata-la-meetup-group/"&gt;new Python Data Science LA&lt;/a&gt; meetup, started by two of us here at &lt;a href="https://datasciencela.github.io/"&gt;DataScience.LA&lt;/a&gt; (our very own &lt;a href="https://datasciencela.github.io/team/#szilard"&gt;Szilard&lt;/a&gt; and &lt;a href="https://datasciencela.github.io/team/#earino"&gt;Eduardo&lt;/a&gt;).&lt;/p&gt;&#10;&lt;p&gt;We&amp;rsquo;ll have 5 speakers at this event, covering various aspects of the Python Data Science ecosystem (NumPy, SciPy, pandas, matplotlib, scikit-learn, NetworkX, NLTK, IPython notebook, etc.)&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://datasciencela.github.io/python-data-science-meetup-data-science-with-python/feature.jpg"/></item><item><title>Packrat presentation at useR! 2014</title><link>https://datasciencela.github.io/packrat-presentation-at-user-2014/</link><pubDate>Fri, 26 Sep 2014 11:25:44 -0700</pubDate><guid>https://datasciencela.github.io/packrat-presentation-at-user-2014/</guid><description>&lt;p&gt;There comes a time in a software toolchain’s lifecycle where the focus shifts from developer productivity and preference to the ability to deploy solutions in production which coexist gracefully in the enterprise. &lt;a href="http://en.wikipedia.org/wiki/Configuration_management"&gt;Configuration management&lt;/a&gt; and dependency management are two of the first points of friction in this transition, as the free-wheeling methods preferred by developers are at odds with the structured methods and isolation desired by administrators, who serve as gatekeepers to enterprise deployment. R is currently at this very point in the transition, in the midst of transformation from a language and environment used primarily in academic research to its growing place in the enterprise. At &lt;a href="http://user2014.stat.ucla.edu/"&gt;useR! 2014&lt;/a&gt; there were a &lt;a href="http://user2014.stat.ucla.edu/abstracts/talks/223_Smith.pdf"&gt;series&lt;/a&gt; &lt;a href="http://user2014.stat.ucla.edu/abstracts/talks/901_Allaire.pdf"&gt;of&lt;/a&gt; &lt;a href="http://user2014.stat.ucla.edu/abstracts/talks/61_Elprin.pdf"&gt;presentations&lt;/a&gt; on how dependency management can be addressed within the R ecosystem, ranging from “provider” side options (e.g. freezing CRAN and private repositories) to the client side options, where a project maintains its own dependencies as part of its codebase.&lt;/p&gt;</description></item><item><title>Yihui Xie, the useR! 2014 Interview</title><link>https://datasciencela.github.io/yihui-xie-the-user-2014-interview/</link><pubDate>Mon, 01 Sep 2014 11:00:48 -0700</pubDate><guid>https://datasciencela.github.io/yihui-xie-the-user-2014-interview/</guid><description>&lt;blockquote&gt;&lt;p&gt;In science consensus is irrelevant. What is relevant is reproducible results. The greatest scientists in history are great precisely because they broke with the consensus.&lt;/p&gt;&#10;&lt;p&gt;&amp;ndash; Michael Crichton&lt;/p&gt;&#10;&lt;/blockquote&gt;&lt;p&gt;&lt;a href="http://yihui.name/en/"&gt;Yihui Xie&lt;/a&gt; intended to make it easier to do his homework, but instead found himself tackling one of the greatest problems in modern science: the reproducibility of results.&lt;/p&gt;</description></item></channel></rss>