{
  "id": 307928,
  "title": "Confidence in your models",
  "url": "/competitions/tensorflow-great-barrier-reef/discussion/307928",
  "author_name": "Dan88",
  "post_date": "2022-02-16T08:26:43.955000",
  "votes": 3,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Unfortunately due to some commitments, I couldn't participate more in the competition. I chose not to modify resolutions and but failed miserably.</p>\n<p>But I was still curious to see how the final LB would look like and what the winning models would be. Following the LB shakeup, I wanted to know how confident were the big gainers in their model? Like what stops you from binning your model and choosing another one?</p>",
  "messages": [
    {
      "id": 1692789,
      "postDate": "2022-02-16T08:26:43.957Z",
      "content": "<p>Unfortunately due to some commitments, I couldn't participate more in the competition. I chose not to modify resolutions and but failed miserably.</p>\n<p>But I was still curious to see how the final LB would look like and what the winning models would be. Following the LB shakeup, I wanted to know how confident were the big gainers in their model? Like what stops you from binning your model and choosing another one?</p>",
      "rawMarkdown": "Unfortunately due to some commitments, I couldn't participate more in the competition. I chose not to modify resolutions and but failed miserably.\n\n But I was still curious to see how the final LB would look like and what the winning models would be. Following the LB shakeup, I wanted to know how confident were the big gainers in their model? Like what stops you from binning your model and choosing another one?",
      "votes": 3
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "1692789": "Unfortunately due to some commitments, I couldn't participate more in the competition. I chose not to modify resolutions and but failed miserably.\n\n But I was still curious to see how the final LB would look like and what the winning models would be. Following the LB shakeup, I wanted to know how confident were the big gainers in their model? Like what stops you from binning your model and choosing another one?"
  }
}