{
  "id": 90880,
  "title": "Penn State Rock Mechanics Lab | Exp.4581",
  "url": "/competitions/LANL-Earthquake-Prediction/discussion/90880",
  "author_name": "",
  "post_date": "2019-04-28T16:13:05.872816900Z",
  "votes": 17,
  "comment_count": 7,
  "views": 0,
  "content": "<p><a href=\"https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\">https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581</a></p>\n\n<p>Splited by events</p>\n\n<p>How load data: <a href=\"https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581\">https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581</a></p>",
  "messages": [
    {
      "id": "524382",
      "postDate": "04/28/2019 16:13:05",
      "content": "<p><a href=\"https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\">https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581</a></p>\n\n<p>Splited by events</p>\n\n<p>How load data: <a href=\"https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581\">https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581</a></p>",
      "rawMarkdown": "https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\n\nSplited by events\n\nHow load data: https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581",
      "votes": null
    },
    {
      "id": "524390",
      "postDate": "04/28/2019 16:56:08",
      "content": "<p>How load data: <a href=\"https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581\">https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581</a></p>",
      "rawMarkdown": "How load data: https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581",
      "votes": null
    },
    {
      "id": "524408",
      "postDate": "04/28/2019 17:44:32",
      "content": "<p>Thank you. This will complicate this competition for sure.</p>",
      "rawMarkdown": "Thank you. This will complicate this competition for sure.",
      "votes": null
    },
    {
      "id": "524426",
      "postDate": "04/28/2019 18:09:22",
      "content": "<p>Data are publicity. So anyone can download it. I only splitted it and convert to numpy format</p>",
      "rawMarkdown": "Data are publicity. So anyone can download it. I only splitted it and convert to numpy format",
      "votes": null
    },
    {
      "id": "524455",
      "postDate": "04/28/2019 19:38:07",
      "content": "<p>Upvote.  Yikes - but thanks.  Does this need to go to the pre-trained model/outside data thread by the contest organizers?</p>",
      "rawMarkdown": "Upvote.  Yikes - but thanks.  Does this need to go to the pre-trained model/outside data thread by the contest organizers?",
      "votes": null
    },
    {
      "id": "524456",
      "postDate": "04/28/2019 19:41:27",
      "content": "<p>Link on raw data posted. <a href=\"https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/77240#516555\">https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/77240#516555</a></p>",
      "rawMarkdown": "Link on raw data posted. https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/77240#516555",
      "votes": null
    },
    {
      "id": "525608",
      "postDate": "05/01/2019 11:50:02",
      "content": "<p>Who got a profit from set ?</p>",
      "rawMarkdown": "Who got a profit from set ?",
      "votes": null
    },
    {
      "id": "526863",
      "postDate": "05/04/2019 01:25:05",
      "content": "<p>Has anyone  been able to use this data  successfully to improve models? I've tried multiple set of transformations  to use them but so far no luck. </p>",
      "rawMarkdown": "Has anyone  been able to use this data  successfully to improve models? I've tried multiple set of transformations  to use them but so far no luck.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 524390,
      "author_name": "leighplt",
      "author_url": "",
      "post_date": "04/28/2019 16:56:08",
      "content": "<p>How load data: <a href=\"https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581\">https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581</a></p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 524408,
      "author_name": "amjad85",
      "author_url": "",
      "post_date": "04/28/2019 17:44:32",
      "content": "<p>Thank you. This will complicate this competition for sure.</p>",
      "votes": null,
      "replies": [
        {
          "id": 524426,
          "author_name": "leighplt",
          "author_url": "",
          "post_date": "04/28/2019 18:09:22",
          "content": "<p>Data are publicity. So anyone can download it. I only splitted it and convert to numpy format</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 524455,
      "author_name": "vettejeep",
      "author_url": "",
      "post_date": "04/28/2019 19:38:07",
      "content": "<p>Upvote.  Yikes - but thanks.  Does this need to go to the pre-trained model/outside data thread by the contest organizers?</p>",
      "votes": null,
      "replies": [
        {
          "id": 524456,
          "author_name": "leighplt",
          "author_url": "",
          "post_date": "04/28/2019 19:41:27",
          "content": "<p>Link on raw data posted. <a href=\"https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/77240#516555\">https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/77240#516555</a></p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 525608,
      "author_name": "leighplt",
      "author_url": "",
      "post_date": "05/01/2019 11:50:02",
      "content": "<p>Who got a profit from set ?</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 526863,
      "author_name": "siavrez",
      "author_url": "",
      "post_date": "05/04/2019 01:25:05",
      "content": "<p>Has anyone  been able to use this data  successfully to improve models? I've tried multiple set of transformations  to use them but so far no luck. </p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "524382": "https://www.kaggle.com/leighplt/laboratory-acoustic-data-exp4581\n\nSplited by events\n\nHow load data: https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581",
    "524390": "How load data: https://www.kaggle.com/leighplt/laboratory-ac-data-exp-p4581",
    "524408": "Thank you. This will complicate this competition for sure.",
    "524426": "Data are publicity. So anyone can download it. I only splitted it and convert to numpy format",
    "524455": "Upvote.  Yikes - but thanks.  Does this need to go to the pre-trained model/outside data thread by the contest organizers?",
    "524456": "Link on raw data posted. https://www.kaggle.com/c/LANL-Earthquake-Prediction/discussion/77240#516555",
    "525608": "Who got a profit from set ?",
    "526863": "Has anyone  been able to use this data  successfully to improve models? I've tried multiple set of transformations  to use them but so far no luck."
  },
  "source": "meta"
}