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    <title>AI on Joris Bukala | Math &amp; ML</title>
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      <title>Understanding Neural Networks</title>
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      <pubDate>Wed, 01 Nov 2023 19:54:22 +0100</pubDate><author>jorisbukalablog@gmail.com (Joris Bukala)</author>
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      <description>&lt;h2 id=&#34;understanding-of-neural-nets-from-first-principles-brain-dump&#34;&gt;&#xA;  Understanding of Neural nets from first-principles: Brain dump&#xA;  &lt;a class=&#34;anchor&#34; href=&#34;#understanding-of-neural-nets-from-first-principles-brain-dump&#34; aria-hidden=&#34;true&#34;&gt;#&lt;/a&gt;&#xA;&lt;/h2&gt;&lt;p&gt;So I was reading my company&amp;rsquo;s IT newsletter the other day where one of the topics was sparse modeling (&lt;a href=&#34;https://www.forbes.com/sites/johnwerner/2023/08/17/sparse-models-the-math-and-a-new-theory-for-ground-breaking-ai/&#34;&gt;discussing this Forbes article&lt;/a&gt;) and it got me thinking again about some things I was reading the past months, about trying to understand how and why (mainly) Deep Learning works.&lt;/p&gt;</description>
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