{
  "fetched_at": "2026-10-24T17:55:12Z",
  "source_url": "https://www.kaggle.com/competitions/cs412-fall-2020-open/data",
  "pages": [
    {
      "name": "data-description",
      "content": "",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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    {
      "name": "Description",
      "content": "We have organized a competition based on the 2017 Kaggle Machine Learning & Data Science Survey dataset. The original data does not have a target label; but the competition is set out to to predict job satisfaction level of Kagglers.\n\nIn this competition, you are expected to predict the JobSatisfaction of a Kaggler, given their job description, level etc. You can find the explanations for data in dataset_explanation.csv, under \"data\" section. Note that the original dataset does not have the \"CompensationScore\" column, which is added manually by us.\n\nThis competition is first designed for the IVAA Hackaton organized by the **Center of Excellence in Data Analytics** and for the CS412 Machine Learning course, at **Sabanci University**.",
      "isPublished": false,
      "hasIsPublished": false,
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    {
      "name": "Evaluation",
      "content": "There are two leaderboards in this competition\n\n**Public Leaderboard**: It consists of 40% (400 samples) of the test data, and it's visible during the competition.\n**Private Leaderboard**: It consists of 60% (600 samples) of the test data, and it will be visible after the deadline.",
      "isPublished": false,
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      "postTitle": "",
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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!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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}