{
  "fetched_at": "2026-10-20T06:50:31Z",
  "source_url": "https://www.kaggle.com/competitions/applications-of-deep-learningwustl-spring-2020b/data",
  "pages": [
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
      "isPublished": false,
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      "postTitle": "",
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    {
      "name": "data-description",
      "content": "<p>The images can be downloaded from the following URL.  The images are all 256x256px. </p>\n\n<a href=\"https://www.kaggle.com/jeffheaton/count-the-paperclips\">Paperclips Images</a>",
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    },
    {
      "name": "Description",
      "content": "This competition asks you to count paperclips on sheets of paper.  Image counting applications are common for many sorts of data analysis.  Images such as you see on Google Maps are frequent targets.  Counting cars, people, trees, houses, water coverage, can all provide valuable information about the demographics of these regions.\n\nFor this competition you are given images of paper covered by paperclips.  Your task is to count the paperclips and return as accurate of a count as possible.  The images are 256x256.\n\nSome images are very easy:\n\n![Test](https://data.heatonresearch.com/kaggle/images/clips-49994.png)\n\nSome images are a little more difficult:\n\n![Test](https://data.heatonresearch.com/kaggle/images/clips-49940.png)\n\nSome images will be really challenging:\n\n![Test](https://data.heatonresearch.com/kaggle/images/clips-49973.png)\n",
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    },
    {
      "name": "Evaluation",
      "content": "<p>The evaluation for the competition is root mean square error (RMSE).  This measures the difference between your predicted number of paperclips and the actual number of paperclips. The actual number of paperclips is always integer; however, you may wish to predict floating-point numbers to account for uncertainty in your model. </p>\n\n<h2>Submission Format</h2>\n<p>You are submitting a CSV file where each row contains an id and your predicted paperclip count. The id's correspond to the file names of the images.  For example, id #1 is clip-1.png</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>id,clip_count\n25001, 37.40416\n25002, 37.40416\n25003, 37.40416\n25004, 37.40416</pre>",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}