{
  "id": 541258,
  "title": "Does it even make sense to participate in the competition without your own server?",
  "url": "/competitions/jane-street-real-time-market-data-forecasting/discussion/541258",
  "author_name": "",
  "post_date": "2024-10-18T11:11:30.034536900Z",
  "votes": 2,
  "comment_count": 2,
  "views": 0,
  "content": "<p>There is a lot of data and I see people complaining about not being able to load all the data into memory at once. <br>\nI'm not sure that working with data piecemeal can be efficient and fast</p>\n<p>Thx for your answers Guys!</p>",
  "messages": [
    {
      "id": "3021313",
      "postDate": "10/18/2024 11:11:30",
      "content": "<p>There is a lot of data and I see people complaining about not being able to load all the data into memory at once. <br>\nI'm not sure that working with data piecemeal can be efficient and fast</p>\n<p>Thx for your answers Guys!</p>",
      "rawMarkdown": "There is a lot of data and I see people complaining about not being able to load all the data into memory at once. \nI'm not sure that working with data piecemeal can be efficient and fast\n\nThx for your answers Guys!",
      "votes": null
    },
    {
      "id": "3021316",
      "postDate": "10/18/2024 11:16:07",
      "content": "<p>You have to be creative with your models, else your data won't fit into your kernel (on Kaggle). A good PC with lots of RAM and a good GPU is a sure advantage here <a href=\"https://www.kaggle.com/egortkachenko\" target=\"_blank\">@egortkachenko</a> </p>",
      "rawMarkdown": "You have to be creative with your models, else your data won't fit into your kernel (on Kaggle). A good PC with lots of RAM and a good GPU is a sure advantage here @egortkachenko",
      "votes": null
    },
    {
      "id": "3073011",
      "postDate": "12/15/2024 23:09:41",
      "content": "<p>so we can use our own server, any guides on how to use that in local machine and how to submit it on Kaggle?</p>",
      "rawMarkdown": "so we can use our own server, any guides on how to use that in local machine and how to submit it on Kaggle?",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 3021316,
      "author_name": "ravi20076",
      "author_url": "",
      "post_date": "10/18/2024 11:16:07",
      "content": "<p>You have to be creative with your models, else your data won't fit into your kernel (on Kaggle). A good PC with lots of RAM and a good GPU is a sure advantage here <a href=\"https://www.kaggle.com/egortkachenko\" target=\"_blank\">@egortkachenko</a> </p>",
      "votes": null,
      "replies": [
        {
          "id": 3073011,
          "author_name": "billyrobert",
          "author_url": "",
          "post_date": "12/15/2024 23:09:41",
          "content": "<p>so we can use our own server, any guides on how to use that in local machine and how to submit it on Kaggle?</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "3021313": "There is a lot of data and I see people complaining about not being able to load all the data into memory at once. \nI'm not sure that working with data piecemeal can be efficient and fast\n\nThx for your answers Guys!",
    "3021316": "You have to be creative with your models, else your data won't fit into your kernel (on Kaggle). A good PC with lots of RAM and a good GPU is a sure advantage here @egortkachenko",
    "3073011": "so we can use our own server, any guides on how to use that in local machine and how to submit it on Kaggle?"
  },
  "source": "meta"
}