{
  "id": 355472,
  "title": "New to Machine Learning or to Kaggle? Check this out.",
  "url": "/competitions/tabular-playground-series-oct-2022/discussion/355472",
  "author_name": "",
  "post_date": "2022-09-26T22:18:40.592531400Z",
  "votes": 10,
  "comment_count": 2,
  "views": 0,
  "content": "<p>New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!</p>\n<p>If you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!</p>\n<p>New to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about <a href=\"https://www.youtube.com/watch?v=aIus8si_Et0\" target=\"_blank\">site etiquette</a>, <a href=\"https://www.youtube.com/watch?v=sEJHyuWKd-s\" target=\"_blank\">Kaggle lingo</a>, and <a href=\"https://www.youtube.com/watch?v=GJBOMWpLpTQ\" target=\"_blank\">how to enter a competition using Kaggle Notebooks</a>.</p>",
  "messages": [
    {
      "id": "1957331",
      "postDate": "09/26/2022 22:18:40",
      "content": "<p>New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!</p>\n<p>If you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!</p>\n<p>New to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about <a href=\"https://www.youtube.com/watch?v=aIus8si_Et0\" target=\"_blank\">site etiquette</a>, <a href=\"https://www.youtube.com/watch?v=sEJHyuWKd-s\" target=\"_blank\">Kaggle lingo</a>, and <a href=\"https://www.youtube.com/watch?v=GJBOMWpLpTQ\" target=\"_blank\">how to enter a competition using Kaggle Notebooks</a>.</p>",
      "rawMarkdown": "New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!\n\nIf you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!\n\nNew to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about [site etiquette](https://www.youtube.com/watch?v=aIus8si_Et0), [Kaggle lingo](https://www.youtube.com/watch?v=sEJHyuWKd-s), and [how to enter a competition using Kaggle Notebooks](https://www.youtube.com/watch?v=GJBOMWpLpTQ).",
      "votes": null
    },
    {
      "id": "1970991",
      "postDate": "10/04/2022 12:04:01",
      "content": "<p>Thank you it was helpful!</p>",
      "rawMarkdown": "Thank you it was helpful!",
      "votes": null
    },
    {
      "id": "1981910",
      "postDate": "10/11/2022 06:18:51",
      "content": "<ol>\n<li><p>How to read such big data into a single dataset? I saw some post of converting it in parquet. Is it the way to go? </p></li>\n<li><p>How to process such big data (e.g. normalize a column)? Do I have to create a Jupiter notebook on the kaggle platform and try to run it on gpu?</p></li>\n</ol>",
      "rawMarkdown": "1. How to read such big data into a single dataset? I saw some post of converting it in parquet. Is it the way to go? \n\n2. How to process such big data (e.g. normalize a column)? Do I have to create a Jupiter notebook on the kaggle platform and try to run it on gpu?",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1970991,
      "author_name": "saipranoy",
      "author_url": "",
      "post_date": "10/04/2022 12:04:01",
      "content": "<p>Thank you it was helpful!</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 1981910,
      "author_name": "osopova",
      "author_url": "",
      "post_date": "10/11/2022 06:18:51",
      "content": "<ol>\n<li><p>How to read such big data into a single dataset? I saw some post of converting it in parquet. Is it the way to go? </p></li>\n<li><p>How to process such big data (e.g. normalize a column)? Do I have to create a Jupiter notebook on the kaggle platform and try to run it on gpu?</p></li>\n</ol>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1957331": "New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!\n\nIf you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!\n\nNew to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about [site etiquette](https://www.youtube.com/watch?v=aIus8si_Et0), [Kaggle lingo](https://www.youtube.com/watch?v=sEJHyuWKd-s), and [how to enter a competition using Kaggle Notebooks](https://www.youtube.com/watch?v=GJBOMWpLpTQ).",
    "1970991": "Thank you it was helpful!",
    "1981910": "1. How to read such big data into a single dataset? I saw some post of converting it in parquet. Is it the way to go? \n\n2. How to process such big data (e.g. normalize a column)? Do I have to create a Jupiter notebook on the kaggle platform and try to run it on gpu?"
  },
  "source": "meta"
}