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  "fetched_at": "2026-10-20T05:20:34Z",
  "source_url": "https://www.kaggle.com/competitions/criots-iot-challenge/data",
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    {
      "name": "data-description",
      "content": "\n<p>The file 'sensor_data.csv' consists of  (randomly shuffled) time-series  readings of the sensors embedded on  criot-hardware which is installed somewhere in a room.</p>\n\n<h2>File descriptions</h2>\n<ul>\n<li><strong>sensor_data.csv</strong> - the time series data </li>\n<li><strong>sample_submission.csv</strong> - a sample submission file in the correct format</li>\n</ul>\n\n<h2>Data fields</h2>\n<ul>\n<li><strong>'Id' </strong>: Unique Id for each time series data point </li>\n<li><strong>'time_stamp' </strong>: HH:MM  ; H: hour , M : minutes</li>\n<li><strong>'sensor_i' </strong>: Readings of raw data observed from i-th sensor (You should have known about the  sensor type through previous questions !! )</li>\n<li> <strong>'flag' </strong>: 1 --> If datapoint is an outlier ; 0--> else\n</ul>\n\n",
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    {
      "name": "Description",
      "content": "<p>Welcome to the final question  of Criot's IoT Challenge hosted as a part of SciTech Week 2021 at IIT Hyderabad </p>\n\n<p>In this question Criot requires you to put in your data science knowledge and help them detect outliers in the time-series data recorded from 4 types of sensors on Criot-hardware.\n</p>\n\n<p>FYI, this is an unsupervised problem statement. Hence you are expected to analyze data carefully and flag the outlier data points and turn in your submissions.</p>\n\n<p>An outlier is defined as in when majority of the sensors show bizarre values when compared to the datapoints in its time-vicinity.<\\p>\n<p>Make sure you join the contest's Whatsapp group (sent in the mail) for further hints/clarifications <\\p>\n\n<p>Top performing teams must share their notebook at the end of the competition whose results should exactly match with the submitted results.<\\p>",
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    {
      "name": "Evaluation",
      "content": "<p> Evaluation will be done based on both public and private leaderboard </p>\n\n<p> AUC (Area under ROC curve) is used as an evaluation metric </p>",
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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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