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		<title>Machine Learning on Jaidev&#39;s Blog</title>
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		<description>Recent content in Machine Learning on Jaidev&#39;s Blog</description>
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				<title>The PlotCaptions Dataset: Automating the Narration of Visual Analytics</title>
				<link>https://jaidevd.com/posts/plotcaptions/</link>
				<pubDate>Mon, 23 Mar 2026 19:20:04 +0530</pubDate>
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				<description>&lt;img class=&#34;article-image&#34; src=&#34;https://jaidevd.com/posts/plotcaptions/snoopy-sherlock.png&#34; alt=&#34;The Data Detective&#34;&gt;&#xA;    &#xA;&#xA;&#xA;&lt;p&gt;I&amp;rsquo;ve always been interested in how we narrate visual analytics. The hardest task&#xA;in dataviz is not analysis or visualization, but figuring out what to&#xA;&lt;em&gt;say&lt;/em&gt; about it. I used to believe that a well designed chart does not need a&#xA;narration. That may be valid, but over the years I&amp;rsquo;ve realized that it is the&#xA;narrative that turns something that is merely pretty and insightful into&#xA;something that is viral. Imagine one of Hans Rosling&amp;rsquo;s talks without him in the&#xA;picture.&lt;/p&gt;</description>
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				<title>Notes on Optimizing Torch Models</title>
				<link>https://jaidevd.com/posts/optimizing-torch-models/</link>
				<pubDate>Thu, 12 Mar 2026 13:00:00 +0530</pubDate>
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				<description>&lt;p&gt;ML researchers are from Mars and the ML engineers responsible for deploying&#xA;models are from Venus. The two have vastly different motivations. The ML&#xA;researcher&amp;rsquo;s job, given a dataset and some compute, is to find the&#xA;lowest possible loss on a task. In this pursuit, no engineering cost is too&#xA;high. No tech debt is too large. Worse still, if they get published, they must&#xA;include their code in their paper. Reproducible research only means that&#xA;everyone be able to reproduce benchmarks and charts from the original paper. It&#xA;usually has very little to do with production.&lt;/p&gt;</description>
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