<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:dc="http://purl.org/dc/elements/1.1/" version="2.0">
  <channel>
    <title>InfoQ - Probability - News</title>
    <link>https://www.infoq.com</link>
    <description>InfoQ Probability News feed</description>
    <item>
      <title>Amazon Releases Fortuna, an Open-Source Library for ML Model Uncertainty Quantification</title>
      <link>https://www.infoq.com/news/2023/01/amazon-fortuna-uncertainty/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Probability-news</link>
      <description>&lt;img src="https://res.infoq.com/news/2023/01/amazon-fortuna-uncertainty/en/headerimage/generatedHeaderImage-1672776134800.jpg"/&gt;&lt;p&gt;AWS announced that Fortuna, an open-source toolkit for ML model uncertainty quantification, has been made generally available. Any trained neural network can be used with the calibration methods offered by Fortuna, such as conformal prediction, to produce calibrated uncertainty estimates.&lt;/p&gt; &lt;i&gt;By Daniel Dominguez&lt;/i&gt;</description>
      <category>AWS</category>
      <category>Machine Learning</category>
      <category>Probability</category>
      <category>Open Source</category>
      <category>TensorFlow</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Wed, 04 Jan 2023 10:55:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2023/01/amazon-fortuna-uncertainty/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Probability-news</guid>
      <dc:creator>Daniel Dominguez</dc:creator>
      <dc:date>2023-01-04T10:55:00Z</dc:date>
      <dc:identifier>/news/2023/01/amazon-fortuna-uncertainty/en</dc:identifier>
    </item>
  </channel>
</rss>
