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      <title>Introduction to Lean for Programmers</title>
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      <description>&lt;p&gt;&lt;em&gt;The syntax and semantics of mathematics&lt;/em&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;img src=&#34;https://rhizomes.pages.dev/images/medium/introduction-to-lean-hero.jpeg&#34; alt=&#34;Infinite chessboard. Image generated by Grok (xAI)&#34;&gt;&lt;/p&gt;&#xA;&lt;p&gt;&lt;em&gt;Infinite chessboard. Image generated by Grok (xAI)&lt;/em&gt;&lt;/p&gt;&#xA;&lt;h2 id=&#34;intro-to-proof-assistants&#34;&gt;Intro to proof assistants&lt;/h2&gt;&#xA;&lt;p&gt;I&amp;rsquo;m a software engineer who transitioned into data science, and I work daily with machine learning algorithms. I&amp;rsquo;m fascinated both by their apparent magic and by the mathematics that underlies them. Pry open any machine learning library and you&amp;rsquo;ll find mathematical tricks involving matrix decompositions, convolutions, Gaussian curves, and more. These, in turn, are built on even more fundamental axioms and rules, such as function application and logic.&lt;/p&gt;</description>
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