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      <title>Building an Email Priority Classifier</title>
      <link>https://nyxox-debug.github.io/nyxox/posts/projects/email-scam-detector/</link>
      <pubDate>Tue, 14 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://nyxox-debug.github.io/nyxox/posts/projects/email-scam-detector/</guid>
      <description>&lt;p&gt;I&amp;rsquo;ve always wondered: what actually makes an email urgent? Is it the length? The words? The tone? So I built TriageAI - a model that classifies incoming emails into priority levels (Urgent, High, Medium, Low) to figure out what deserves attention &lt;em&gt;right now&lt;/em&gt;.&lt;/p&gt;</description>
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      <title>I Built an Artificial Life Simulation in C++</title>
      <link>https://nyxox-debug.github.io/nyxox/posts/projects/artificial-life-simulation/</link>
      <pubDate>Sat, 04 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://nyxox-debug.github.io/nyxox/posts/projects/artificial-life-simulation/</guid>
      <description>&lt;p&gt;I&amp;rsquo;ve always been curious about emergence. How does organized, purposeful behavior arise from simple rules? How does a colony of ants, with no central planner, manage to build complex structures and find food efficiently?&lt;/p&gt;&#xA;&lt;p&gt;So I built &lt;strong&gt;OKIOS&lt;/strong&gt; — named after the Greek &lt;em&gt;οἶκος&lt;/em&gt;, meaning home or habitat. It&amp;rsquo;s a 3D artificial life simulation where creatures with neural-network brains learn to survive entirely on their own. No predefined roles. No hand-coded behaviors. Just pressure, time, and mutation.&lt;/p&gt;</description>
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      <title>Building a Neural Network Framework from Scratch</title>
      <link>https://nyxox-debug.github.io/nyxox/posts/projects/deep-learning-framework-scratch/</link>
      <pubDate>Tue, 24 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://nyxox-debug.github.io/nyxox/posts/projects/deep-learning-framework-scratch/</guid>
      <description>&lt;p&gt;I use PyTorch every day at work. It&amp;rsquo;s incredible - but I&amp;rsquo;ve always wondered: how does it actually work under the hood? How does &lt;code&gt;backward()&lt;/code&gt; actually compute gradients through a neural network?&lt;/p&gt;&#xA;&lt;p&gt;So I built my own minimal deep learning framework called &lt;strong&gt;Synap&lt;/strong&gt;. It&amp;rsquo;s written in C++ for performance, with Python bindings via pybind11. No external ML libraries - just raw tensor operations and automatic differentiation from scratch.&lt;/p&gt;</description>
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      <title>Building a 3D Renderer from Scratch</title>
      <link>https://nyxox-debug.github.io/nyxox/posts/projects/3d-renderer-scratch/</link>
      <pubDate>Tue, 27 Jan 2026 00:00:00 +0000</pubDate>
      <guid>https://nyxox-debug.github.io/nyxox/posts/projects/3d-renderer-scratch/</guid>
      <description>&lt;p&gt;I&amp;rsquo;ve always been curious about what happens inside game engines when they render a 3D model. You know that feeling when you use Unity or Unreal without understanding what&amp;rsquo;s actually happening on the GPU? That&amp;rsquo;s exactly why I decided to build my own 3D renderer from scratch using C++ and OpenGL.&lt;/p&gt;&#xA;&lt;p&gt;No engines. No magic. Just raw graphics programming.&lt;/p&gt;</description>
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      <title>I Built a Programming Language in Go</title>
      <link>https://nyxox-debug.github.io/nyxox/posts/projects/programming-language-go/</link>
      <pubDate>Mon, 29 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://nyxox-debug.github.io/nyxox/posts/projects/programming-language-go/</guid>
      <description>&lt;p&gt;I&amp;rsquo;ve always been fascinated by programming languages. How does code actually become a running program? What happens when you type &lt;code&gt;let x = 5;&lt;/code&gt; in a REPL?&lt;/p&gt;&#xA;&lt;p&gt;So I built my own. Meet &lt;strong&gt;Bat&lt;/strong&gt; - a tiny interpreted programming language written entirely in Go. It&amp;rsquo;s not useful for production, but it taught me how interpreters actually work.&lt;/p&gt;</description>
    </item>
    <item>
      <title>Building a GitHub Analyzer with Go and Python</title>
      <link>https://nyxox-debug.github.io/nyxox/posts/projects/github-analyzer-go-python/</link>
      <pubDate>Fri, 05 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://nyxox-debug.github.io/nyxox/posts/projects/github-analyzer-go-python/</guid>
      <description>&lt;p&gt;Ever wanted to quickly understand what a GitHub repository looks like without cloning and exploring it yourself? I built a tool that does exactly that - paste any GitHub URL, and it analyzes the entire codebase, extracting complexity metrics, code structure, and language distribution.&lt;/p&gt;&#xA;&lt;p&gt;The best part? It combines Go and Python in a way that showcases how to pick the right tool for each job.&lt;/p&gt;</description>
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