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      <title>Mind Garden</title>
      <link>https://thealex.ac/garden</link>
      <description>Last 10 notes on Mind Garden</description>
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    <title>Consequential Predictions</title>
    <link>https://thealex.ac/garden/Consequential-Predictions/</link>
    <guid>https://thealex.ac/garden/Consequential-Predictions/</guid>
    <description><![CDATA[ Consequential Predictions A prediction is consequential when it influences a decision that materially affects people, risk, safety, money, or access to public services. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Data Generating Process</title>
    <link>https://thealex.ac/garden/Data-Generating-Process/</link>
    <guid>https://thealex.ac/garden/Data-Generating-Process/</guid>
    <description><![CDATA[ Data Generating Process A data generating process is the real-world mechanism that produces the observations in a dataset. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Decision Intelligence</title>
    <link>https://thealex.ac/garden/Decision-Intelligence/</link>
    <guid>https://thealex.ac/garden/Decision-Intelligence/</guid>
    <description><![CDATA[ Decision Intelligence Decision intelligence treats modeling as part of a decision process rather than an isolated prediction task. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Digital Gardens</title>
    <link>https://thealex.ac/garden/Digital-Gardens/</link>
    <guid>https://thealex.ac/garden/Digital-Gardens/</guid>
    <description><![CDATA[ Digital Gardens A digital garden is a collection of notes that can grow over time rather than a reverse-chronological blog. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Domain Knowledge in Modeling</title>
    <link>https://thealex.ac/garden/Domain-Knowledge-in-Modeling/</link>
    <guid>https://thealex.ac/garden/Domain-Knowledge-in-Modeling/</guid>
    <description><![CDATA[ Domain Knowledge in Modeling Domain knowledge is information about the world that is not naturally available as rows and columns. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>From Drafts to Garden Notes</title>
    <link>https://thealex.ac/garden/From-Drafts-to-Garden-Notes/</link>
    <guid>https://thealex.ac/garden/From-Drafts-to-Garden-Notes/</guid>
    <description><![CDATA[ From Drafts to Garden Notes This cluster was seeded from unpublished Hugo drafts in content/blog/: what-utilities-taught-me-about-the-limitations-of-machine-learning.md why-ml-needs-probabilistic-programming.md Rather than publishing those drafts directly, the useful material was split into linked g... ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Interpretable Statistical Models</title>
    <link>https://thealex.ac/garden/Interpretable-Statistical-Models/</link>
    <guid>https://thealex.ac/garden/Interpretable-Statistical-Models/</guid>
    <description><![CDATA[ Interpretable Statistical Models Interpretable statistical models make their assumptions and relationships available for inspection. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Lead Service Line Replacement</title>
    <link>https://thealex.ac/garden/Lead-Service-Line-Replacement/</link>
    <guid>https://thealex.ac/garden/Lead-Service-Line-Replacement/</guid>
    <description><![CDATA[ Lead Service Line Replacement Lead service line replacement is a useful example of machine learning in public infrastructure. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Machine Learning Culture</title>
    <link>https://thealex.ac/garden/Machine-Learning-Culture/</link>
    <guid>https://thealex.ac/garden/Machine-Learning-Culture/</guid>
    <description><![CDATA[ Machine Learning Culture Machine learning inherits part of its culture from artificial intelligence: build systems that perform tasks humans can do, then evaluate whether the output is good. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
  </item><item>
    <title>Machine Learning in Public Infrastructure</title>
    <link>https://thealex.ac/garden/Machine-Learning-in-Public-Infrastructure/</link>
    <guid>https://thealex.ac/garden/Machine-Learning-in-Public-Infrastructure/</guid>
    <description><![CDATA[ Machine Learning in Public Infrastructure Public infrastructure is a demanding setting for machine learning because predictions often mediate access to scarce inspection, repair, or response capacity. ]]></description>
    <pubDate>Mon, 11 May 2026 01:47:25 GMT</pubDate>
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