{
  "fetched_at": "2026-10-20T02:33:18Z",
  "source_url": "https://www.kaggle.com/competitions/applai-competition-a1/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<p>It serves as an excellent introduction to implementing machine learning algorithms because it requires rudimentary data cleaning, has an easily understandable list of variables and sits at an optimal size between being to toyish and too cumbersome.\n\nThe data contains information from the 1990 California census. So although it may not help you with predicting current housing prices like the Zillow Zestimate dataset, it does provide an accessible introductory dataset for teaching people about the basics of machine learning..</p>\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<li>etc...</li>\n</ul>\n\n<p>Participants should be able to answer questions like these after reading the data description: What files do I need? What should I expect the data format to be? What am I predicting? What acroynms will I encounter?</p>\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<li>etc...</li>\n</ul>\n<h2>Data fields</h2>\n<ul>\n<li><strong>longitude</strong> - A measure of how far west a house is; a higher value is farther west</li>\n<li><strong>latitude</strong> - A measure of how far north a house is; a higher value is farther north</li>\n<li><strong>housing Median Age</strong> -Median age of a house within a block; a lower number is a newer building</li>\n<li><strong>total Rooms</strong> -Total number of rooms within a block</li>\n<li><strong>total BedRooms</strong> -Total number of bedrooms within a block</li>\n<li><strong>population</strong> -Total number of people residing within a block</li>\n<li><strong>households</strong> -Total number of households, a group of people residing within a home unit, for a block</li>\n<li><strong>medianIncome</strong> -Median income for households within a block of houses (measured in tens of thousands of US Dollars)\n</li>\n<li><strong>medianHouseValue</strong> -Median house value for households within a block (measured in US Dollars)</li>\n<li><strong>oceanProximity</strong> -Location of the house w.r.t ocean/sea</li>\n\n<li>etc...</li>\n</ul>",
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    {
      "name": "Description",
      "content": "<p>It serves as an excellent introduction to implementing machine learning algorithms because it requires rudimentary data cleaning, has an easily understandable list of variables and sits at an optimal size between being to toyish and too cumbersome.\n\nThe data contains information from the 1990 California census. So although it may not help you with predicting current housing prices like the Zillow Zestimate dataset, it does provide an accessible introductory dataset for teaching people about the basics of machine learning..</p>",
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    {
      "name": "Evaluation",
      "content": "<h2>Submission Format</h2>\n<p> submission files should contain two columns: House_ID and median_house_value.</p>\n<p>The file should contain a header and have the following format:</p>\n<pre>House_ID,median_house_value<br>1,1<br></pre>",
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    {
      "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!",
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}