{
  "id": 186016,
  "title": "convert kernel to csv competition",
  "url": "/competitions/lyft-motion-prediction-autonomous-vehicles/discussion/186016",
  "author_name": "laol",
  "post_date": "2020-09-22T21:13:49.566000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p><a href=\"https://www.kaggle.com/lao777/fast-submission-valid-for-public-private-lb\" target=\"_blank\">https://www.kaggle.com/lao777/fast-submission-valid-for-public-private-lb</a></p>\n<p>MOTIVATION: formally speaking, we are participating in kernel competition, but reality is telling us different things - it's casual predict locally then submit csv comp</p>\n<p>OVERVIEW: this code will make:</p>\n<ol>\n<li>create private dataset with your submission.csv file</li>\n<li>create private kernel</li>\n<li>attach dataset from step 1 to kernel from step 2</li>\n<li>kernel will transfer submission.csv from step 1 as submission for competition</li>\n</ol>\n<p>PREPARATION<br>\nbefore execution of this script you have to </p>\n<ol>\n<li>install kaggle python package</li>\n<li>autorize in kaggle cli<br>\n<a href=\"https://github.com/Kaggle/kaggle-api#api-credentials\" target=\"_blank\">https://github.com/Kaggle/kaggle-api#api-credentials</a><br>\n3 put this code into \"make_submit.py\" in \"make_submit\" forlder in any place, which you wish</li>\n</ol>\n<p>HOWTO use<br>\npython make_submit/make_submit.py --path relative_or_absolute_path/sub.csv<br>\nyou have to be sure that sub.csv has proper format for submission</p>",
  "messages": [
    {
      "id": 1022976,
      "postDate": "2020-09-22T21:13:49.567Z",
      "content": "<p><a href=\"https://www.kaggle.com/lao777/fast-submission-valid-for-public-private-lb\" target=\"_blank\">https://www.kaggle.com/lao777/fast-submission-valid-for-public-private-lb</a></p>\n<p>MOTIVATION: formally speaking, we are participating in kernel competition, but reality is telling us different things - it's casual predict locally then submit csv comp</p>\n<p>OVERVIEW: this code will make:</p>\n<ol>\n<li>create private dataset with your submission.csv file</li>\n<li>create private kernel</li>\n<li>attach dataset from step 1 to kernel from step 2</li>\n<li>kernel will transfer submission.csv from step 1 as submission for competition</li>\n</ol>\n<p>PREPARATION<br>\nbefore execution of this script you have to </p>\n<ol>\n<li>install kaggle python package</li>\n<li>autorize in kaggle cli<br>\n<a href=\"https://github.com/Kaggle/kaggle-api#api-credentials\" target=\"_blank\">https://github.com/Kaggle/kaggle-api#api-credentials</a><br>\n3 put this code into \"make_submit.py\" in \"make_submit\" forlder in any place, which you wish</li>\n</ol>\n<p>HOWTO use<br>\npython make_submit/make_submit.py --path relative_or_absolute_path/sub.csv<br>\nyou have to be sure that sub.csv has proper format for submission</p>",
      "rawMarkdown": "https://www.kaggle.com/lao777/fast-submission-valid-for-public-private-lb\n\nMOTIVATION: formally speaking, we are participating in kernel competition, but reality is telling us different things - it's casual predict locally then submit csv comp\n\nOVERVIEW: this code will make:\n1. create private dataset with your submission.csv file\n2. create private kernel\n3. attach dataset from step 1 to kernel from step 2\n4. kernel will transfer submission.csv from step 1 as submission for competition\n\nPREPARATION\nbefore execution of this script you have to \n1. install kaggle python package\n2. autorize in kaggle cli\nhttps://github.com/Kaggle/kaggle-api#api-credentials\n3 put this code into \"make_submit.py\" in \"make_submit\" forlder in any place, which you wish\n\nHOWTO use\npython make_submit/make_submit.py --path relative_or_absolute_path/sub.csv\nyou have to be sure that sub.csv has proper format for submission",
      "votes": 1
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "1022976": "https://www.kaggle.com/lao777/fast-submission-valid-for-public-private-lb\n\nMOTIVATION: formally speaking, we are participating in kernel competition, but reality is telling us different things - it's casual predict locally then submit csv comp\n\nOVERVIEW: this code will make:\n1. create private dataset with your submission.csv file\n2. create private kernel\n3. attach dataset from step 1 to kernel from step 2\n4. kernel will transfer submission.csv from step 1 as submission for competition\n\nPREPARATION\nbefore execution of this script you have to \n1. install kaggle python package\n2. autorize in kaggle cli\nhttps://github.com/Kaggle/kaggle-api#api-credentials\n3 put this code into \"make_submit.py\" in \"make_submit\" forlder in any place, which you wish\n\nHOWTO use\npython make_submit/make_submit.py --path relative_or_absolute_path/sub.csv\nyou have to be sure that sub.csv has proper format for submission"
  }
}