{
  "fetched_at": "2026-10-24T17:57:24Z",
  "source_url": "https://www.kaggle.com/competitions/choose-tutors/data",
  "pages": [
    {
      "name": "rules",
      "content": "You can only use these imports:\n\n```\nimport numpy as np  \nimport pandas as pd  \nfrom sklearn.model_selection import train_test_split  \nimport matplotlib.pyplot as plt  \nimport seaborn as sns\n```",
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      "hasIsPublished": false,
      "postTitle": "",
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    {
      "name": "data-description",
      "content": "",
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    {
      "name": "Description",
      "content": "<p>In this competition your task will be to predict the probability for a tutor to be a proper one for preparing for the math exam. You will be given two datasets: train.csv (contains all features and the target) and test.csv (only features).</p>\n-------------------------------------------------------------------------------------------------------------------\n<p>Ваша задача этом соревновании - предсказать вероятность того, подойдет ли репетитор для подготовки к экзамену по математике. Вам будут даны два датасета: train.csv (содержит признаки и целевую переменную) и test.csv (только признаки).</p>",
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      "hasIsPublished": false,
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    },
    {
      "name": "Evaluation",
      "content": "The evaluation metric is [ROC AUC](https://en.wikipedia.org/wiki/Receiver_operating_characteristic)\n\n----------------------------\n\nМетрика для оценки – [ROC AUC](https://ru.wikipedia.org/wiki/ROC-%D0%BA%D1%80%D0%B8%D0%B2%D0%B0%D1%8F)",
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}