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    <loc>http://www.tanglyweb.com/home/2016/7/31/porto-taxi</loc>
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      <image:title>Data Science - táxis de Portugal</image:title>
      <image:caption>A 2D histogram of the organically hailed trips throughout the Porto metropolitan area.</image:caption>
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      <image:title>Data Science - táxis de Portugal</image:title>
      <image:caption>Notice that as we increase the number of clusters K, the total squared distance between rides and their nearest cluster naturally decreases. At some point, around K=5 or 6, it is clear that adding more clusters offers little additional explanatory valuable.</image:caption>
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      <image:title>Data Science - táxis de Portugal</image:title>
      <image:caption>A heat map of the destinations visited overlaid with a Voronoi diagram which indicates the classification boundaries for the K=6 clusters.</image:caption>
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      <image:caption>Transition matrix. Square in (row=i, column=j) represents the percentage of rides arriving in cluster j that originate in clutser i.</image:caption>
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      <image:title>Data Science - táxis de Portugal</image:title>
      <image:caption>A histogram-scatter of the as-the-crow-flies distance to that traveled by the taxi.</image:caption>
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      <image:title>Mountains - Skiing the Grand Traverse</image:title>
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      <image:title>Mountains - Skiing the Grand Traverse</image:title>
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      <image:title>Mountains - Skiing the Grand Traverse</image:title>
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      <image:title>Mountains - Skiing the Grand Traverse</image:title>
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      <image:title>Mountains - Skiing the Grand Traverse</image:title>
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    <loc>http://www.tanglyweb.com/about</loc>
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    <lastmod>2020-05-03</lastmod>
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      <image:title>About Me - Evan Welch</image:title>
      <image:caption>I have a degree in Physics, a background in derivatives trading, and am now a data scientist in Seattle. Here you can find my musings, both quantitative and fluffy.</image:caption>
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