{
  "id": 177726,
  "title": "1st Place Solution Full Code Released",
  "url": "/competitions/siim-isic-melanoma-classification/discussion/177726",
  "author_name": "Qishen Ha",
  "post_date": "2020-08-27T04:44:37.763000",
  "votes": 77,
  "comment_count": 21,
  "views": 0,
  "content": "<p>Hi all,</p>\n<p>We've finished cleanning up the FULL code of our pipeline and here it is:</p>\n<p><a href=\"https://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution\" target=\"_blank\">https://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution</a></p>",
  "messages": [
    {
      "id": 987195,
      "postDate": "2020-08-27T04:44:37.763Z",
      "content": "<p>Hi all,</p>\n<p>We've finished cleanning up the FULL code of our pipeline and here it is:</p>\n<p><a href=\"https://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution\" target=\"_blank\">https://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution</a></p>",
      "rawMarkdown": "Hi all,\n\nWe've finished cleanning up the FULL code of our pipeline and here it is:\n\nhttps://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution\n",
      "votes": 76
    },
    {
      "id": 994265,
      "postDate": "2020-09-01T13:48:30.610Z",
      "content": "<p>Thanks a lot, this is very informative and helpful <a href=\"https://www.kaggle.com/haqishen\" target=\"_blank\">@haqishen</a> !</p>",
      "rawMarkdown": "Thanks a lot, this is very informative and helpful @haqishen !",
      "votes": 1
    },
    {
      "id": 988227,
      "postDate": "2020-08-27T22:29:18.757Z",
      "content": "<p>Thanks a lot for sharing...\nThat's such an invaluable contribution!!\nCheers!</p>",
      "rawMarkdown": "Thanks a lot for sharing...\nThat's such an invaluable contribution!!\nCheers!",
      "votes": 1
    },
    {
      "id": 987743,
      "postDate": "2020-08-27T13:38:16.040Z",
      "content": "<p>Thanks for sharing your knowledge with kaggle community.</p>",
      "rawMarkdown": "Thanks for sharing your knowledge with kaggle community.",
      "votes": 1
    },
    {
      "id": 1169555,
      "postDate": "2021-01-25T15:05:59.377Z",
      "content": "<p>Thanks for sharing! This will be a great learning opportunity :)</p>",
      "rawMarkdown": "Thanks for sharing! This will be a great learning opportunity :)"
    },
    {
      "id": 1140883,
      "postDate": "2021-01-06T10:44:40.677Z",
      "content": "<p>Very good!<br>\nWhat is the key ideas of solution?</p>",
      "rawMarkdown": "Very good!\nWhat is the key ideas of solution?"
    },
    {
      "id": 1004463,
      "postDate": "2020-09-09T18:21:42.833Z",
      "content": "<p>I also want to ask, why do not need to use weights in nn.CrossEntropyLoss to account for imbalance numbers of labels.</p>",
      "rawMarkdown": "I also want to ask, why do not need to use weights in nn.CrossEntropyLoss to account for imbalance numbers of labels."
    },
    {
      "id": 996495,
      "postDate": "2020-09-03T10:33:29.177Z",
      "content": "<p>Thanks for your help. Will analyse the code, thanks again for sharing.</p>",
      "rawMarkdown": "Thanks for your help. Will analyse the code, thanks again for sharing."
    },
    {
      "id": 995785,
      "postDate": "2020-09-02T19:09:06.197Z",
      "content": "<p>Thank you for sharing your work man, I hope one day I can code like you!</p>",
      "rawMarkdown": "Thank you for sharing your work man, I hope one day I can code like you!"
    },
    {
      "id": 997135,
      "postDate": "2020-09-03T19:13:12.123Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 995713,
      "postDate": "2020-09-02T17:57:26.173Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 992921,
      "postDate": "2020-08-31T14:18:28.070Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 989525,
      "postDate": "2020-08-28T21:55:27.170Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 989162,
      "postDate": "2020-08-28T15:25:43.730Z",
      "rawMarkdown": "",
      "isDeleted": true
    },
    {
      "id": 989146,
      "postDate": "2020-08-28T15:19:56.137Z",
      "rawMarkdown": "",
      "votes": 1,
      "isDeleted": true
    },
    {
      "id": 987236,
      "postDate": "2020-08-27T05:26:05.367Z",
      "content": "<p>Thanks a lot:)</p>",
      "rawMarkdown": "Thanks a lot:)",
      "votes": 3
    },
    {
      "id": 989201,
      "postDate": "2020-08-28T16:01:41.910Z",
      "content": "<p>Thanks for sharing! </p>",
      "rawMarkdown": "Thanks for sharing! ",
      "votes": 1
    },
    {
      "id": 996410,
      "postDate": "2020-09-03T09:17:08.687Z",
      "content": "<p>thank you so much!</p>",
      "rawMarkdown": "thank you so much!"
    },
    {
      "id": 996406,
      "postDate": "2020-09-03T09:12:24.693Z",
      "content": "<p>Thanks for sharing!</p>",
      "rawMarkdown": "Thanks for sharing!\n\n"
    },
    {
      "id": 994869,
      "postDate": "2020-09-02T03:10:50.723Z",
      "content": "<p>Thanks for sharing</p>",
      "rawMarkdown": "Thanks for sharing"
    },
    {
      "id": 994854,
      "postDate": "2020-09-02T02:38:35.007Z",
      "content": "<p>Thanks for sharing the awesome work!</p>",
      "rawMarkdown": "Thanks for sharing the awesome work!"
    },
    {
      "id": 994113,
      "postDate": "2020-09-01T11:27:49.373Z",
      "content": "<p>Thanks for sharing!</p>",
      "rawMarkdown": "Thanks for sharing!"
    }
  ],
  "comments": [
    {
      "id": 994265,
      "author_name": "Shyam R",
      "author_url": "",
      "post_date": "2020-09-01T13:48:30.610000",
      "content": "<p>Thanks a lot, this is very informative and helpful <a href=\"https://www.kaggle.com/haqishen\" target=\"_blank\">@haqishen</a> !</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 988227,
      "author_name": "Ramon M. Ferreira",
      "author_url": "",
      "post_date": "2020-08-27T22:29:18.757000",
      "content": "<p>Thanks a lot for sharing...\nThat's such an invaluable contribution!!\nCheers!</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 987743,
      "author_name": "Karan",
      "author_url": "",
      "post_date": "2020-08-27T13:38:16.040000",
      "content": "<p>Thanks for sharing your knowledge with kaggle community.</p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 1169555,
      "author_name": "권 진혁 (Jin Kwon)",
      "author_url": "",
      "post_date": "2021-01-25T15:05:59.377000",
      "content": "<p>Thanks for sharing! This will be a great learning opportunity :)</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 1140883,
      "author_name": "ZavodRobotov",
      "author_url": "",
      "post_date": "2021-01-06T10:44:40.677000",
      "content": "<p>Very good!<br>\nWhat is the key ideas of solution?</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 1004463,
      "author_name": "Dat Duong2",
      "author_url": "",
      "post_date": "2020-09-09T18:21:42.833000",
      "content": "<p>I also want to ask, why do not need to use weights in nn.CrossEntropyLoss to account for imbalance numbers of labels.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 996495,
      "author_name": "ardatci",
      "author_url": "",
      "post_date": "2020-09-03T10:33:29.177000",
      "content": "<p>Thanks for your help. Will analyse the code, thanks again for sharing.</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 995785,
      "author_name": "Maurício Melo de Moraes Rego",
      "author_url": "",
      "post_date": "2020-09-02T19:09:06.197000",
      "content": "<p>Thank you for sharing your work man, I hope one day I can code like you!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 997135,
      "author_name": "",
      "author_url": "",
      "post_date": "2020-09-03T19:13:12.123000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 995713,
      "author_name": "",
      "author_url": "",
      "post_date": "2020-09-02T17:57:26.173000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 992921,
      "author_name": "",
      "author_url": "",
      "post_date": "2020-08-31T14:18:28.070000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 989525,
      "author_name": "",
      "author_url": "",
      "post_date": "2020-08-28T21:55:27.170000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 989162,
      "author_name": "",
      "author_url": "",
      "post_date": "2020-08-28T15:25:43.730000",
      "content": "",
      "votes": 0,
      "replies": []
    },
    {
      "id": 989146,
      "author_name": "",
      "author_url": "",
      "post_date": "2020-08-28T15:19:56.137000",
      "content": "",
      "votes": 1,
      "replies": []
    },
    {
      "id": 987236,
      "author_name": "Ninja Coding",
      "author_url": "",
      "post_date": "2020-08-27T05:26:05.367000",
      "content": "<p>Thanks a lot:)</p>",
      "votes": 3,
      "replies": []
    },
    {
      "id": 989201,
      "author_name": "Moon",
      "author_url": "",
      "post_date": "2020-08-28T16:01:41.910000",
      "content": "<p>Thanks for sharing! </p>",
      "votes": 1,
      "replies": []
    },
    {
      "id": 996410,
      "author_name": "jamescasia",
      "author_url": "",
      "post_date": "2020-09-03T09:17:08.687000",
      "content": "<p>thank you so much!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 996406,
      "author_name": "Codefupanda",
      "author_url": "",
      "post_date": "2020-09-03T09:12:24.693000",
      "content": "<p>Thanks for sharing!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 994869,
      "author_name": "Hritik Akolkar",
      "author_url": "",
      "post_date": "2020-09-02T03:10:50.723000",
      "content": "<p>Thanks for sharing</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 994854,
      "author_name": "권 진혁 (Jin Kwon)",
      "author_url": "",
      "post_date": "2020-09-02T02:38:35.007000",
      "content": "<p>Thanks for sharing the awesome work!</p>",
      "votes": 0,
      "replies": []
    },
    {
      "id": 994113,
      "author_name": "Jafe",
      "author_url": "",
      "post_date": "2020-09-01T11:27:49.373000",
      "content": "<p>Thanks for sharing!</p>",
      "votes": 0,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "987195": "Hi all,\n\nWe've finished cleanning up the FULL code of our pipeline and here it is:\n\nhttps://github.com/haqishen/SIIM-ISIC-Melanoma-Classification-1st-Place-Solution\n",
    "994265": "Thanks a lot, this is very informative and helpful @haqishen !",
    "988227": "Thanks a lot for sharing...\nThat's such an invaluable contribution!!\nCheers!",
    "987743": "Thanks for sharing your knowledge with kaggle community.",
    "1169555": "Thanks for sharing! This will be a great learning opportunity :)",
    "1140883": "Very good!\nWhat is the key ideas of solution?",
    "1004463": "I also want to ask, why do not need to use weights in nn.CrossEntropyLoss to account for imbalance numbers of labels.",
    "996495": "Thanks for your help. Will analyse the code, thanks again for sharing.",
    "995785": "Thank you for sharing your work man, I hope one day I can code like you!",
    "997135": "",
    "995713": "",
    "992921": "",
    "989525": "",
    "989162": "",
    "989146": "",
    "987236": "Thanks a lot:)",
    "989201": "Thanks for sharing! ",
    "996410": "thank you so much!",
    "996406": "Thanks for sharing!\n\n",
    "994869": "Thanks for sharing",
    "994854": "Thanks for sharing the awesome work!",
    "994113": "Thanks for sharing!"
  }
}