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  "fetched_at": "2026-10-20T05:13:27Z",
  "source_url": "https://www.kaggle.com/competitions/applications-of-deep-learningwustl-spring-2019/data",
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      "name": "rules",
      "content": "<!-- Begin Base Rules -->\n<h3>One account per participant</h3>\n<p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\n<h3>No private sharing outside teams</h3>\n<p>\n    Privately sharing code or data outside of teams is not permitted.\n    It's okay to share code if made available to all participants on the forums.\n</p>\n<h3>Team Mergers</h3>\n<p>Team mergers are not allowed in this competition.</p>\n\n<h3>Team Limits</h3>\n<p>Up to 5 individuals per team.  Teams will be defined prior to competition and should not change.</p>\n<h3>Submission Limits</h3>\n<p>You may submit a maximum of 20 entries per day.</p>\n<p>You may select up to 2 final submissions for judging.</p>\n<h3>Competition Timeline</h3>\n<p>Start Date: <strong>As specified in syllabus.</strong></p>\n<p>Entry Deadline: <strong>None</strong></p>\n<p>End Date: <strong>As specified in syllabus.</strong></p>\n<!-- End Base Rules -->",
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      "content": "<p>This data set contains zipcodes and a business score for each zipcode.  You should join the dataset to the government data sources for zipcodes indicated on the main conference page.  A list of data sources are provided on the main competition overview page. </p>\n\n<h2>File Descriptions</h2>\n<ul>\n<li><strong>train.csv</strong> - the training set</li>\n<li><strong>test.csv</strong> - the test set</li>\n<li><strong>sampleSubmission.csv</strong> - a sample submission file in the correct format</li>\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>id</strong> - The row ID.</li>\n<li><strong>zipcode</strong> - The zipcode.</li>\n<li><strong>score</strong> - The exact nature of the \"business score\" (score column) is not disclosed. It is connected to the business/market saturation of a zipcode</li>\n</ul>",
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      "name": "Description",
      "content": "This is a project from the course [T81-855: Applications of Deep Learning at Washington University in St. Louis](https://sites.wustl.edu/jeffheaton/t81-558/). All students must create a Kaggle account and submit a solution. If you are a student, once you have submitted your solution entry log into Canvas (at WUSTL) and submit a single file telling me your Kaggle name on the leaderboard (you do not need to register to Kaggle with your real name). This competition will be visible to the public, so there may be non-student submissions as well as student.\n\nThis competition see if you can predict a \"business score\" for each of the USA zipcodes.  The exact nature of the \"business score\" (score column) is not disclosed.  It is connected to the business/market saturation of a zipcode.  The data files given to you on Kaggle will not be sufficient to predict.  You must augment your data with additional files.  Some suggestions include:\n\n<ul>\n<li><a href=\"https://www.irs.gov/statistics/soi-tax-stats-individual-income-tax-statistics-2016-zip-code-data-soi\">US Government public data for \"SOI Tax Stats - Individual Income Tax Statistics\"</a>\n<li><a href=\"https://www.data.gov/\">Data.GOV: The home of the U.S. Government’s open data</a>\n</ul>\n\n[This video][1] describes the competition.\n\n\n  [1]: https://www.youtube.com/watch?v=GaKo-9c532c",
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      "name": "Evaluation",
      "content": "Evaluation\nMarkdown\n Published?\n Delete Page\nStyling with Markdown supported\n<p>Submissions are evaluated on <a href=\"https://www.kaggle.com/wiki/RootMeanSquaredError\" target=\"_blank\">Root-Mean-Squared-Error (RMSE)</a> between the submitted outcome and the the observed outcome from the data set. </p>\n<p>\\[ \\text{RMSE} = \\sqrt{ \\frac{1}{n} \\sum_{i=1}^n (y_i - \\hat{y}_i)^2} \\]</p>\n<h1>Submission File</h1>\n<p>For each Id in the test set, you must predict the value of the outcome variable. The file should contain a header and have the following format:</p>\n<pre><code>id,score</code><br /><code>146,14</code><br /><code>147,32</code><br /><code>148,83.235743</code><br /><code>etc.</code></pre>\n",
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