{
  "fetched_at": "2026-10-19T19:12:38Z",
  "source_url": "https://www.kaggle.com/competitions/data-science-capstone-project-2023/data",
  "pages": [
    {
      "name": "data-description",
      "content": "## Columns\n1. id -> Airbnb Listing Id\n2. name -> Airbnb Listing Name\n3. host_id -> Host Name who is hosting the Airbnb Listing\n4. host_name -> Name of the host\n5. neighbourhood_group -> Name of Borough in New York\n6. neighbourhood -> Name of Neighbourhood in New York\n7. latitude -> Latitude of Airbnb Listing\n8. longitude -> Longitude of Airbnb Listing\n9. room_type -> Type of Room\n10. minimum_nights -> Minimum number of nights to stay for that particular Airbnb Listing\n11. number_of_reviews -> Number of Reviews of that particular Airbnb Listing\n12. last_review -> Date of the last review of that particular listing\n13. reviews_per_month -> Average Reviews each month\n14. floor → The floor of the airbnb listing\n15. noise (dB) → Average sound levels recorded in dB\n16. Location -> Address of the airbnb listing\n17. price -> Price of that particular Airbnb Listing",
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    {
      "name": "Description",
      "content": "#About Dataset\n##Context\nSince 2008, guests and hosts have used Airbnb to expand on traveling possibilities and present a more unique, personalized way of experiencing the world. This dataset describes the listing activity and metrics in NYC, NY for 2019.\n\n##Content\nThis data file includes all needed information to find out more about hosts, geographical availability, and necessary metrics to make predictions and draw conclusions.\n\n\n##Inspiration\nWhat can we learn about different hosts and areas?\nWhat can we learn from predictions? (ex: locations, prices, reviews, etc)\nWhich hosts are the busiest and why?\nIs there any noticeable difference in traffic among different areas and what could be the reason for it?\nHow does proximity to different points of interest impact the prices?\n\n## Task\nThe task is to predict the prices of Airbnb listings.\n\n## Acknowledgments\nThis public dataset is part of Airbnb, and the original source can be found on this [website](http://insideairbnb.com/)",
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    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is Root Mean Squared Error.  RMSE measures the square root of the average of the squares of the errors—that is, the square root of the average squared difference between the estimated values and the actual value.\n\n## Submission Format\n\nThe submission files should contain two columns: `Id` and `Price`. \n\nThe file should contain a header and have the following format:\n```\nId,Price\n1,1\n```",
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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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