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      <title>Richard Hua</title>
      <link>https://richardhua.dev</link>
      <description>Last 10 notes on Richard Hua</description>
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    <title>AI Agent for Steam</title>
    <link>https://richardhua.dev/Projects/ai-agent-steam</link>
    <guid>https://richardhua.dev/Projects/ai-agent-steam</guid>
    <description><![CDATA[ A conversational game discovery engine with hybrid search, image-based retrieval, and real-time Steam data integration. ]]></description>
    <pubDate>Sun, 05 Apr 2026 23:44:56 GMT</pubDate>
  </item><item>
    <title>C++ Game Engine</title>
    <link>https://richardhua.dev/Projects/cpp-game-engine</link>
    <guid>https://richardhua.dev/Projects/cpp-game-engine</guid>
    <description><![CDATA[ A from-scratch 2D game engine in C++ with A* pathfinding, a visitor-pattern collision system, and a Pac-Man clone that exercises every subsystem. ]]></description>
    <pubDate>Sun, 22 Mar 2026 22:12:45 GMT</pubDate>
  </item><item>
    <title>Richard Hua</title>
    <link>https://richardhua.dev/</link>
    <guid>https://richardhua.dev/</guid>
    <description><![CDATA[  ]]></description>
    <pubDate>Sun, 22 Mar 2026 19:31:57 GMT</pubDate>
  </item><item>
    <title>GPU Store</title>
    <link>https://richardhua.dev/Projects/gpu-store</link>
    <guid>https://richardhua.dev/Projects/gpu-store</guid>
    <description><![CDATA[ A full-stack compute storefront with Stripe Checkout, Redis-backed webhook safety, and the kind of backend concerns that show up in real payment flows. ]]></description>
    <pubDate>Wed, 18 Mar 2026 21:13:00 GMT</pubDate>
  </item><item>
    <title>RAG for Obsidian</title>
    <link>https://richardhua.dev/Projects/rag-obs</link>
    <guid>https://richardhua.dev/Projects/rag-obs</guid>
    <description><![CDATA[ A retrieval-augmented study workflow for querying Obsidian vaults, citing source notes, and generating flashcards from uploaded markdown. ]]></description>
    <pubDate>Wed, 18 Mar 2026 21:13:00 GMT</pubDate>
  </item><item>
    <title>Projects</title>
    <link>https://richardhua.dev/Projects/</link>
    <guid>https://richardhua.dev/Projects/</guid>
    <description><![CDATA[ Selected builds across retrieval systems, developer tooling, and product-focused full-stack work. ]]></description>
    <pubDate>Mon, 16 Mar 2026 20:07:40 GMT</pubDate>
  </item><item>
    <title>Variable Importance</title>
    <link>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Variable-Importance</link>
    <guid>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Variable-Importance</guid>
    <description><![CDATA[ To measure variable importance, we can measure how much each variable improves model predictions. These evaluated on incMSE and incNodePurity. ]]></description>
    <pubDate>Thu, 29 Jan 2026 00:09:13 GMT</pubDate>
  </item><item>
    <title>Bagging</title>
    <link>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Bagging</link>
    <guid>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Bagging</guid>
    <description><![CDATA[ Combines multiple models on random subsets of data to to reduce variance. Bagging is a type of Ensemble Method. ]]></description>
    <pubDate>Thu, 29 Jan 2026 00:08:03 GMT</pubDate>
  </item><item>
    <title>Ensemble Methods</title>
    <link>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Ensemble-Methods</link>
    <guid>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Ensemble-Methods</guid>
    <description><![CDATA[ Bagging Boosting Techniques which combine the predictions of multiple models to improve overall predictive performance. ]]></description>
    <pubDate>Thu, 29 Jan 2026 00:08:03 GMT</pubDate>
  </item><item>
    <title>Out of Bag Observations</title>
    <link>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Out-of-Bag-Observations</link>
    <guid>https://richardhua.dev/Machine-Learning/Ensemble-Methods/Out-of-Bag-Observations</guid>
    <description><![CDATA[ Observations that are not included in the bootstrap sample during bagging are referred to as Out of Bag Observations. ]]></description>
    <pubDate>Thu, 29 Jan 2026 00:08:03 GMT</pubDate>
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