{
  "fetched_at": "2026-10-20T05:53:53Z",
  "source_url": "https://www.kaggle.com/competitions/bits-f464-l0/data",
  "pages": [
    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "data-description",
      "content": "This dataset contains the rating of products. Based on the features predict a rating (1-10). Note that you can predict decimal ratings. \n\nFile descriptions:\n\n- train.csv - the training set\n- test.csv - the test set\n- sample_submission.csv - a sample submission file in the correct format\n",
      "isPublished": false,
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      "postTitle": "",
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    },
    {
      "name": "Description",
      "content": "\nYour task is to predict the rating for a product from given features. RMSE will be used to evaluate your predictions. \n<br>\nWhen you submit your predictions only 50% of them will be evaluated and you can see your score on the Public Leaderboard. At the end of the contest, the remaining 50% will be evaluated and final standings will be displayed on Private Leaderboard. \n<br>\nThis is competition is **non-evaluative** and is meant just as a practice lab.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "The evaluation metric for this competition is the Root Mean Squared Error (RMSE).",
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      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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      "hasMimeType": false
    }
  ]
}