atom.xml

<?xml version="1.0" encoding="UTF-8" ?>

<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <atom:link href="https://blog.alvarezrosa.com/rss.xml"
               rel="self"
               type="application/rss+xml" />

    <title>David Álvarez Rosa | Personal Blog</title>
    <link>https://blog.alvarezrosa.com/</link>
    <language>en</language>
    <description>
      My personal Blog site. Stuff I've written, mainly about Technology and
      Mathematics. By David Álvarez Rosa.
    </description>

    <image>
      <url>https://david.alvarezrosa.com/img/favicon.ico</url>
      <title>Icon for David Álvarez Rosa Personal Website.</title>
      <link>https://blog.alvarezrosa.com/</link>
    </image>
    <webMaster>webmaster@alvarezrosa.com (David Álvarez Rosa)</webMaster>

    <item>
      <title>Hello World!</title>
      <guid>https://blog.alvarezrosa.com/hello-world.php</guid>
      <link>https://blog.alvarezrosa.com/hello-world.php</link>
      <author>webmaster@alvarezrosa.com (David Álvarez Rosa)</author>
      <pubDate>Thu, 07 Nov 2019 16:53:04 -0500</pubDate>
      <category>Blog</category>
      <category>Entry</category>
      <category>Greeting</category>
      <description><![CDATA[ As when starting anything new in CS, <em>Hello
      World!</em> This blog post is dated the day my personal website
      <strong>went live</strong>. Either way, hello again. If you happen to be
      interested, feel free to <strong>subscribe</strong> using the above RSS
      file or to get in touch by clicking on the link in the homepage.
      ]]></description>
    </item>

    <item>
      <title>Implementing a Neural Network from scratch - Part 1</title>
      <guid>https://blog.alvarezrosa.com/neural-network-part1.php</guid>
      <link>https://blog.alvarezrosa.com/neural-network-part1.php</link>
      <author>webmaster@alvarezrosa.com (David Álvarez Rosa)</author>
      <pubDate>Sat, 11 Apr 2020 16:53:04 -0500</pubDate>
      <category>Neural Network</category>
      <category>AI</category>
      <category>Deep Learning</category>
      <category>Machine Learning</category>
      <category>C++</category>
      <category>Implementation</category>
      <category>Scratch</category>
      <description><![CDATA[ <strong class="abstract">Abstract</strong>. The
      first entry of this blog series of implementing a Neural Network in C++
      will be covering the <strong>mathematical theory</strong> behind the fully
      connected layered artificial neural networks. We will start by defining
      its <a href="#sec:topology" title="Scroll to network topology section.">
      topology</a> and its core <strong>components</strong>. Then we will dicuss
      how a neural network works (namely <a href="#sec:forward" title="Scroll to
      feed forward section."> forward propagation</a>) This blog entry will
      finish by <strong>reformulating</strong> the learning problem from a
      mathematical optimization point of view and deriving the
      <em>well-known</em> <a href="#sec:backward" title="Scroll to backward
      propagation section"> backward propagation</a> formula.  ]]></description>
    </item>
  </channel>
</rss>