{
  "id": 82490,
  "title": "It was no fluke",
  "url": "/competitions/humpback-whale-identification/discussion/82490",
  "author_name": "",
  "post_date": "2019-03-01T18:45:26.801093900Z",
  "votes": 4,
  "comment_count": 2,
  "views": 0,
  "content": "<p>The task of this competition was very difficult and really cooked my melon, but applying machine learning techniques to wildlife conservation is a noble porpoise. The competitors and their solutions were just top-notch.  Early on I was afraid my models would fall off the trailing edge of the LB, but thanks to the effective orcastration of ideas kindly shared in the discussions the predictions ended up being killer.  Sometimes it was stressful, every time a model diverged made me blubber, but I always dived back in as seeing the map5 increase warmed my blood. I wont spout any more nonsense, gg everyone, now back to the breach. </p>",
  "messages": [
    {
      "id": "481714",
      "postDate": "03/01/2019 18:45:26",
      "content": "<p>The task of this competition was very difficult and really cooked my melon, but applying machine learning techniques to wildlife conservation is a noble porpoise. The competitors and their solutions were just top-notch.  Early on I was afraid my models would fall off the trailing edge of the LB, but thanks to the effective orcastration of ideas kindly shared in the discussions the predictions ended up being killer.  Sometimes it was stressful, every time a model diverged made me blubber, but I always dived back in as seeing the map5 increase warmed my blood. I wont spout any more nonsense, gg everyone, now back to the breach. </p>",
      "rawMarkdown": "The task of this competition was very difficult and really cooked my melon, but applying machine learning techniques to wildlife conservation is a noble porpoise. The competitors and their solutions were just top-notch.  Early on I was afraid my models would fall off the trailing edge of the LB, but thanks to the effective orcastration of ideas kindly shared in the discussions the predictions ended up being killer.  Sometimes it was stressful, every time a model diverged made me blubber, but I always dived back in as seeing the map5 increase warmed my blood. I wont spout any more nonsense, gg everyone, now back to the breach.",
      "votes": null
    },
    {
      "id": "481969",
      "postDate": "03/02/2019 05:47:09",
      "content": "<p>Great job !!</p>",
      "rawMarkdown": "Great job !!",
      "votes": null
    },
    {
      "id": "482289",
      "postDate": "03/02/2019 16:28:42",
      "content": "<p>Congratulations <a href=\"/interneuron\">@interneuron</a>  </p>",
      "rawMarkdown": "Congratulations @interneuron",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 481969,
      "author_name": "priteshshrivastava",
      "author_url": "",
      "post_date": "03/02/2019 05:47:09",
      "content": "<p>Great job !!</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 482289,
      "author_name": "karthik7395",
      "author_url": "",
      "post_date": "03/02/2019 16:28:42",
      "content": "<p>Congratulations <a href=\"/interneuron\">@interneuron</a>  </p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "481714": "The task of this competition was very difficult and really cooked my melon, but applying machine learning techniques to wildlife conservation is a noble porpoise. The competitors and their solutions were just top-notch.  Early on I was afraid my models would fall off the trailing edge of the LB, but thanks to the effective orcastration of ideas kindly shared in the discussions the predictions ended up being killer.  Sometimes it was stressful, every time a model diverged made me blubber, but I always dived back in as seeing the map5 increase warmed my blood. I wont spout any more nonsense, gg everyone, now back to the breach.",
    "481969": "Great job !!",
    "482289": "Congratulations @interneuron"
  },
  "source": "meta"
}