<?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>Emma Beauxis-Aussalet</title>
    <description/>
    <link>https://speakerdeck.com/ebeauxis</link>
    <atom:link rel="self" type="application/rss+xml" href="https://speakerdeck.com/ebeauxis.rss"/>
    <lastBuildDate>2019-12-16 07:32:52 -0500</lastBuildDate>
    <item>
      <title>Making Classification Error and Bias Transparent and Understandable</title>
      <description></description>
      <media:content url="https://files.speakerdeck.com/presentations/0f56ac15348b4b5fb2a2610c902629ec/preview_slide_0.jpg?14482036" type="image/jpeg" medium="image"/>
      <content:encoded></content:encoded>
      <pubDate>Sat, 14 Dec 2019 00:00:00 -0500</pubDate>
      <link>https://speakerdeck.com/ebeauxis/making-classification-error-and-bias-transparent-and-understandable</link>
      <guid>https://speakerdeck.com/ebeauxis/making-classification-error-and-bias-transparent-and-understandable</guid>
    </item>
  </channel>
</rss>
