<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet href="/feed.rss.xml" type="text/xsl" media="screen"?>
<rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:media="http://search.yahoo.com/mrss/" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Michael Becker</title>
    <description/>
    <link>https://speakerdeck.com/beckerfuffle</link>
    <atom:link rel="self" type="application/rss+xml" href="https://speakerdeck.com/beckerfuffle.rss"/>
    <lastBuildDate>2016-03-01 20:02:17 -0500</lastBuildDate>
    <item>
      <title>Data Science: It’s Easy as Py!</title>
      <description>Over the last several years, many amazing Python projects have been created for working with data, making Python one of the top languages for data scientists. In this talk, Michael Becker will cover all five stages of the OSEMN data science process, and several Python libraries that can be used at each stage. To demo, he will illustrate the creation of a language classification algorithm, using Wikipedia articles.</description>
      <media:content url="https://files.speakerdeck.com/presentations/4a79f5096bfd4d539a81dd3e8aeff772/preview_slide_0.jpg?5938690" type="image/jpeg" medium="image"/>
      <content:encoded>Over the last several years, many amazing Python projects have been created for working with data, making Python one of the top languages for data scientists. In this talk, Michael Becker will cover all five stages of the OSEMN data science process, and several Python libraries that can be used at each stage. To demo, he will illustrate the creation of a language classification algorithm, using Wikipedia articles.</content:encoded>
      <pubDate>Thu, 25 Feb 2016 00:00:00 -0500</pubDate>
      <link>https://speakerdeck.com/beckerfuffle/data-science-its-easy-as-py-1</link>
      <guid>https://speakerdeck.com/beckerfuffle/data-science-its-easy-as-py-1</guid>
    </item>
    <item>
      <title>Data Science: It’s Easy as Py! (With Notes)</title>
      <description>Over the last several years, many amazing Python projects have been created for working with data, making Python one of the top languages for data scientists. In this talk, Michael Becker will cover all five stages of the OSEMN &lt;http://www.dataists.com/2010/09/a-taxonomy-of-data-science/&gt; data science process, and several Python libraries that can be used at each stage. To demo, he will illustrate the creation of a language classification algorithm, using Wikipedia articles. </description>
      <media:content url="https://files.speakerdeck.com/presentations/618e7f55148d4e21ad40962f9a4d9169/preview_slide_0.jpg?5938546" type="image/jpeg" medium="image"/>
      <content:encoded>Over the last several years, many amazing Python projects have been created for working with data, making Python one of the top languages for data scientists. In this talk, Michael Becker will cover all five stages of the OSEMN &lt;http://www.dataists.com/2010/09/a-taxonomy-of-data-science/&gt; data science process, and several Python libraries that can be used at each stage. To demo, he will illustrate the creation of a language classification algorithm, using Wikipedia articles. </content:encoded>
      <pubDate>Thu, 25 Feb 2016 00:00:00 -0500</pubDate>
      <link>https://speakerdeck.com/beckerfuffle/data-science-its-easy-as-py-with-notes</link>
      <guid>https://speakerdeck.com/beckerfuffle/data-science-its-easy-as-py-with-notes</guid>
    </item>
  </channel>
</rss>
