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      <title>Egor Dmitriev</title>
      <link>https://egordmitriev.dev</link>
      <description>Last 10 notes on Egor Dmitriev</description>
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    <title>Building Boosters: A Gradient Boosting Library from Scratch</title>
    <link>https://egordmitriev.dev/blog/2026-01-25-boosters</link>
    <guid>https://egordmitriev.dev/blog/2026-01-25-boosters</guid>
    <description><![CDATA[ The story of building a gradient boosting library in Rust—from dissecting XGBoost models to achieving performance parity and beyond. ]]></description>
    <pubDate>Tue, 03 Feb 2026 00:00:00 GMT</pubDate>
  </item><item>
    <title>Regularization and Hyperparameter Tuning</title>
    <link>https://egordmitriev.dev/blog/2026-01-20-regularization</link>
    <guid>https://egordmitriev.dev/blog/2026-01-20-regularization</guid>
    <description><![CDATA[ A practical guide to configuring gradient boosting: learning rate, tree depth, regularization, and systematic tuning strategies. ]]></description>
    <pubDate>Sun, 01 Feb 2026 00:00:00 GMT</pubDate>
  </item><item>
    <title>Blog</title>
    <link>https://egordmitriev.dev/blog/</link>
    <guid>https://egordmitriev.dev/blog/</guid>
    <description><![CDATA[ A collection of articles about machine learning, data engineering, and software development. ]]></description>
    <pubDate>Tue, 27 Jan 2026 19:39:37 GMT</pubDate>
  </item><item>
    <title>Egor Dmitriev</title>
    <link>https://egordmitriev.dev/</link>
    <guid>https://egordmitriev.dev/</guid>
    <description><![CDATA[ Projects Boosters — A high-performance gradient boosting library for Python and Rust . ]]></description>
    <pubDate>Tue, 27 Jan 2026 19:39:37 GMT</pubDate>
  </item><item>
    <title>Boosters</title>
    <link>https://egordmitriev.dev/projects/boosters</link>
    <guid>https://egordmitriev.dev/projects/boosters</guid>
    <description><![CDATA[ A high-performance gradient boosting library for Python and Rust ]]></description>
    <pubDate>Tue, 27 Jan 2026 19:39:37 GMT</pubDate>
  </item><item>
    <title>Projects</title>
    <link>https://egordmitriev.dev/projects/</link>
    <guid>https://egordmitriev.dev/projects/</guid>
    <description><![CDATA[ Projects A showcase of my open-source work and side projects. Featured 🚀 Boosters A high-performance gradient boosting library for Python and Rust. ]]></description>
    <pubDate>Tue, 27 Jan 2026 19:39:37 GMT</pubDate>
  </item><item>
    <title>Series</title>
    <link>https://egordmitriev.dev/series/</link>
    <guid>https://egordmitriev.dev/series/</guid>
    <description><![CDATA[ A collection of multi-part blog series exploring technical topics in depth. ]]></description>
    <pubDate>Tue, 27 Jan 2026 19:39:37 GMT</pubDate>
  </item><item>
    <title>Inside Gradient Boosting</title>
    <link>https://egordmitriev.dev/series/inside-gradient-boosting</link>
    <guid>https://egordmitriev.dev/series/inside-gradient-boosting</guid>
    <description><![CDATA[ A deep dive into how XGBoost and LightGBM work — from first principles to implementation details. ]]></description>
    <pubDate>Tue, 27 Jan 2026 19:39:37 GMT</pubDate>
  </item><item>
    <title>Trees and the Split Gain Formula</title>
    <link>https://egordmitriev.dev/blog/2026-01-10-trees-and-split-gain</link>
    <guid>https://egordmitriev.dev/blog/2026-01-10-trees-and-split-gain</guid>
    <description><![CDATA[ How decision trees fit into gradient boosting: from second-order Taylor expansion to the split gain formula that powers XGBoost and LightGBM. ]]></description>
    <pubDate>Tue, 27 Jan 2026 00:00:00 GMT</pubDate>
  </item><item>
    <title>XGBoost vs LightGBM: A Practical Comparison</title>
    <link>https://egordmitriev.dev/blog/2026-01-22-xgboost-vs-lightgbm</link>
    <guid>https://egordmitriev.dev/blog/2026-01-22-xgboost-vs-lightgbm</guid>
    <description><![CDATA[ When to choose XGBoost vs LightGBM: speed, accuracy, features, and practical recommendations based on your use case. ]]></description>
    <pubDate>Thu, 22 Jan 2026 00:00:00 GMT</pubDate>
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