{
  "id": 554389,
  "title": "How many features did you use for final model within Kaggle Notebook?",
  "url": "/competitions/jane-street-real-time-market-data-forecasting/discussion/554389",
  "author_name": "",
  "post_date": "2025-01-01T08:53:06.979274Z",
  "votes": -1,
  "comment_count": 1,
  "views": 0,
  "content": "<p>The data size and memory limit in kaggle notebook obviously in this competition has capped the training data size and the features one can make, and not everyone is accessible to bigger machines for offline training.  </p>\n<p>Wonder how many features have you used in the submission using Kaggle notebook for training.</p>",
  "messages": [
    {
      "id": "3085512",
      "postDate": "01/01/2025 08:53:06",
      "content": "<p>The data size and memory limit in kaggle notebook obviously in this competition has capped the training data size and the features one can make, and not everyone is accessible to bigger machines for offline training.  </p>\n<p>Wonder how many features have you used in the submission using Kaggle notebook for training.</p>",
      "rawMarkdown": "The data size and memory limit in kaggle notebook obviously in this competition has capped the training data size and the features one can make, and not everyone is accessible to bigger machines for offline training.  \n\nWonder how many features have you used in the submission using Kaggle notebook for training.",
      "votes": null
    },
    {
      "id": "3085768",
      "postDate": "01/01/2025 14:59:34",
      "content": "<p>You can use the TPU Accelerator and save your work to datasets for submission without accelerator </p>",
      "rawMarkdown": "You can use the TPU Accelerator and save your work to datasets for submission without accelerator",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 3085768,
      "author_name": "jazivxt",
      "author_url": "",
      "post_date": "01/01/2025 14:59:34",
      "content": "<p>You can use the TPU Accelerator and save your work to datasets for submission without accelerator </p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "3085512": "The data size and memory limit in kaggle notebook obviously in this competition has capped the training data size and the features one can make, and not everyone is accessible to bigger machines for offline training.  \n\nWonder how many features have you used in the submission using Kaggle notebook for training.",
    "3085768": "You can use the TPU Accelerator and save your work to datasets for submission without accelerator"
  },
  "source": "meta"
}