{
  "fetched_at": "2026-10-20T04:36:11Z",
  "source_url": "https://www.kaggle.com/competitions/gdsc-nsut-recruitment/data",
  "pages": [
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      "name": "data-description",
      "content": "## Files\n\n*   **final_train.csv** - the training set\n*   **final_test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n\n## Columns\n\n*   `id` - definition of example_id\n*   `feature_1` - definition of feature_1\n* 'target' - target variable which you need to predict for test data.\n",
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    {
      "name": "Description",
      "content": "**GDSC NSUT** recruitment competition\n\n**Task**\nYou have to predict the value of the 'target'.\n\n**Rules for competition:**\n\n- You can form a team of 2 in the contest. [Team should be visible in Kaggle leaderboard too] \n   How to form a team --> Goto Teams panel --> search username ---> invite in team\n- The top 10 teams in the Private Leaderboard will be invited for the interview round.\n- If you feel a little overwhelmed with deploying ML models, you can also submit your analysis code on the same dataset by mailing us. 5 will be selected in this task.\n**- Maximum of 15 submissions are allowed per day for each team.\n**- You can fork our tutorial [notebook](https://www.kaggle.com/nischaydnk/gdsc-notebook-from-host) and make changes in that too. \n- Googling is allowed ofc :))\n- How to submit through a notebook: https://www.kaggle.com/dansbecker/submitting-from-a-kernel , https://www.youtube.com/watch?v=1G6eehnBUwI\n\nAll the best!!!",
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      "name": "Evaluation",
      "content": "The evaluation metric for this competition is Area Under the ROC Curve (AUC): https://en.wikipedia.org/wiki/Receiver_operating_characteristic\n\n## Submission Format\n\n**For every id in the test dataset**, submission files should contain two columns: `id` and `target`. \n\nThe file should contain a header and have the following format:\n```\nid,target\n0,0.9\n1,0.5\n2,0.2\n```",
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    {
      "name": "rules",
      "content": "Rules:\n\n - Don't cheat! If someone is found cheating, then tumhari jagha priyanshu ML mentee\n - Apply yourself!\n - Have fun!",
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