{
  "id": 90626,
  "title": "Medium article, code and 15th place solution",
  "url": "/competitions/histopathologic-cancer-detection/writeups/antiflu-medium-article-code-and-15th-place-solutio",
  "author_name": "",
  "post_date": "2019-04-25T12:00:12.798592900Z",
  "votes": 5,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Hi all,\nI guess we were not really focused on this competition, so everything we did was just training a lot of NN's and blending them all together. However, I made a <a href=\"https://github.com/azkalot1/histopathologic_cancer_detection\">repo </a>with a minimal example + a small <a href=\"https://medium.com/@sergeykolchenko/histopathologic-cancer-detection-as-image-classification-using-pytorch-557aab058449\">post </a> with couple of ideas and examples. Hope it helps someone :) </p>",
  "messages": [
    {
      "id": "523020",
      "postDate": "04/25/2019 12:00:12",
      "content": "<p>Hi all,\nI guess we were not really focused on this competition, so everything we did was just training a lot of NN's and blending them all together. However, I made a <a href=\"https://github.com/azkalot1/histopathologic_cancer_detection\">repo </a>with a minimal example + a small <a href=\"https://medium.com/@sergeykolchenko/histopathologic-cancer-detection-as-image-classification-using-pytorch-557aab058449\">post </a> with couple of ideas and examples. Hope it helps someone :) </p>",
      "rawMarkdown": "Hi all,\nI guess we were not really focused on this competition, so everything we did was just training a lot of NN's and blending them all together. However, I made a [repo ](https://github.com/azkalot1/histopathologic_cancer_detection)with a minimal example + a small [post ](https://medium.com/@sergeykolchenko/histopathologic-cancer-detection-as-image-classification-using-pytorch-557aab058449) with couple of ideas and examples. Hope it helps someone :)",
      "votes": null
    },
    {
      "id": "553150",
      "postDate": "06/15/2019 07:58:25",
      "content": "<p>Thanks for sharing fellow kaggler</p>",
      "rawMarkdown": "Thanks for sharing fellow kaggler",
      "votes": null
    },
    {
      "id": "572011",
      "postDate": "07/10/2019 10:47:16",
      "content": "<p>Thanks for the share </p>",
      "rawMarkdown": "Thanks for the share",
      "votes": null
    },
    {
      "id": "730278",
      "postDate": "01/27/2020 10:04:05",
      "content": "<p>may I know your hardware config?</p>",
      "rawMarkdown": "may I know your hardware config?",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 553150,
      "author_name": "pratiksharm",
      "author_url": "",
      "post_date": "06/15/2019 07:58:25",
      "content": "<p>Thanks for sharing fellow kaggler</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 572011,
      "author_name": "gsdeepakkumar",
      "author_url": "",
      "post_date": "07/10/2019 10:47:16",
      "content": "<p>Thanks for the share </p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 730278,
      "author_name": "masoudmzb",
      "author_url": "",
      "post_date": "01/27/2020 10:04:05",
      "content": "<p>may I know your hardware config?</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "523020": "Hi all,\nI guess we were not really focused on this competition, so everything we did was just training a lot of NN's and blending them all together. However, I made a [repo ](https://github.com/azkalot1/histopathologic_cancer_detection)with a minimal example + a small [post ](https://medium.com/@sergeykolchenko/histopathologic-cancer-detection-as-image-classification-using-pytorch-557aab058449) with couple of ideas and examples. Hope it helps someone :)",
    "553150": "Thanks for sharing fellow kaggler",
    "572011": "Thanks for the share",
    "730278": "may I know your hardware config?"
  },
  "source": "meta"
}