{
  "id": 138051,
  "title": "DCASE 2020 Challenge and Task 2 Contents Available!",
  "url": "/competitions/freesound-audio-tagging-2019/discussion/138051",
  "author_name": "",
  "post_date": "2020-03-23T14:36:53.031931600Z",
  "votes": 7,
  "comment_count": 4,
  "views": 0,
  "content": "<p>Dear all,</p>\n\n<p>First, I wish you are safe during this difficult time.</p>\n\n<p>As I wrote in title, DCASE 2020 challenge is going on.\nUnfortunately no task is held in Kaggle this year,\nthen I'm sharing contents specifically prepared for task 2.\nThis time the task is Anomaly Detection (which I'm currently focusing on).</p>\n\n<h2>Datasets &amp; Notebooks</h2>\n\n<ul>\n<li><a href=\"https://www.kaggle.com/daisukelab/dc2020task2\">DCASE 2020 Task 2 Unofficial Copy</a>\n<ul><li><a href=\"https://www.kaggle.com/daisukelab/dcase2020-task2-baseline-ae-starter\">DCASE2020 Task2 Baseline AE Starter</a></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dcase-2020-task-2-eda\">DCASE 2020 Task 2 EDA</a></li></ul></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dc2020task2prep\">DCASE 2020 Task 2 Preprocessed (for CNN)</a>\n<ul><li><a href=\"https://www.kaggle.com/daisukelab/dcase2020-task2-cnn-ae-starter\">DCASE2020 Task2 CNN-AE Starter</a></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dcase-2020-task-2-preprocessed-eda\">DCASE 2020 Task 2 Preprocessed EDA</a></li></ul></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dc2020task2added\">DCASE 2020 Task 2 Additinal Set Unofficial Copy</a> *NEW\n<ul><li><a href=\"https://www.kaggle.com/daisukelab/dcase-2020-task-2-additional-training-dataset-eda\">DCASE 2020 Task 2 Additional Training Dataset EDA</a> *NEW</li></ul></li>\n</ul>\n\n<p>You can use these dataset copies and develop your solutions as same as Kaggle competitions.\nI wish you all keep safety, and may you have time to enjoy hacking datasets as usual...</p>\n\n<h3>UPDATE</h3>\n\n<ul>\n<li>Apr 2nd, 2020 Officially additional training dataset was released, then added unofficial copy here!</li>\n</ul>",
  "messages": [
    {
      "id": "783639",
      "postDate": "03/23/2020 14:36:53",
      "content": "<p>Dear all,</p>\n\n<p>First, I wish you are safe during this difficult time.</p>\n\n<p>As I wrote in title, DCASE 2020 challenge is going on.\nUnfortunately no task is held in Kaggle this year,\nthen I'm sharing contents specifically prepared for task 2.\nThis time the task is Anomaly Detection (which I'm currently focusing on).</p>\n\n<h2>Datasets &amp; Notebooks</h2>\n\n<ul>\n<li><a href=\"https://www.kaggle.com/daisukelab/dc2020task2\">DCASE 2020 Task 2 Unofficial Copy</a>\n<ul><li><a href=\"https://www.kaggle.com/daisukelab/dcase2020-task2-baseline-ae-starter\">DCASE2020 Task2 Baseline AE Starter</a></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dcase-2020-task-2-eda\">DCASE 2020 Task 2 EDA</a></li></ul></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dc2020task2prep\">DCASE 2020 Task 2 Preprocessed (for CNN)</a>\n<ul><li><a href=\"https://www.kaggle.com/daisukelab/dcase2020-task2-cnn-ae-starter\">DCASE2020 Task2 CNN-AE Starter</a></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dcase-2020-task-2-preprocessed-eda\">DCASE 2020 Task 2 Preprocessed EDA</a></li></ul></li>\n<li><a href=\"https://www.kaggle.com/daisukelab/dc2020task2added\">DCASE 2020 Task 2 Additinal Set Unofficial Copy</a> *NEW\n<ul><li><a href=\"https://www.kaggle.com/daisukelab/dcase-2020-task-2-additional-training-dataset-eda\">DCASE 2020 Task 2 Additional Training Dataset EDA</a> *NEW</li></ul></li>\n</ul>\n\n<p>You can use these dataset copies and develop your solutions as same as Kaggle competitions.\nI wish you all keep safety, and may you have time to enjoy hacking datasets as usual...</p>\n\n<h3>UPDATE</h3>\n\n<ul>\n<li>Apr 2nd, 2020 Officially additional training dataset was released, then added unofficial copy here!</li>\n</ul>",
      "rawMarkdown": "Dear all,\n\nFirst, I wish you are safe during this difficult time.\n\nAs I wrote in title, DCASE 2020 challenge is going on.\nUnfortunately no task is held in Kaggle this year,\nthen I'm sharing contents specifically prepared for task 2.\nThis time the task is Anomaly Detection (which I'm currently focusing on).\n\n## Datasets &amp; Notebooks\n- [DCASE 2020 Task 2 Unofficial Copy](https://www.kaggle.com/daisukelab/dc2020task2)\n    - [DCASE2020 Task2 Baseline AE Starter](https://www.kaggle.com/daisukelab/dcase2020-task2-baseline-ae-starter)\n    - [DCASE 2020 Task 2 EDA](https://www.kaggle.com/daisukelab/dcase-2020-task-2-eda)\n- [DCASE 2020 Task 2 Preprocessed (for CNN)](https://www.kaggle.com/daisukelab/dc2020task2prep)\n    - [DCASE2020 Task2 CNN-AE Starter](https://www.kaggle.com/daisukelab/dcase2020-task2-cnn-ae-starter)\n    - [DCASE 2020 Task 2 Preprocessed EDA](https://www.kaggle.com/daisukelab/dcase-2020-task-2-preprocessed-eda)\n- [DCASE 2020 Task 2 Additinal Set Unofficial Copy](https://www.kaggle.com/daisukelab/dc2020task2added) *NEW\n    - [DCASE 2020 Task 2 Additional Training Dataset EDA](https://www.kaggle.com/daisukelab/dcase-2020-task-2-additional-training-dataset-eda) *NEW\n\nYou can use these dataset copies and develop your solutions as same as Kaggle competitions.\nI wish you all keep safety, and may you have time to enjoy hacking datasets as usual...\n\n### UPDATE\n\n- Apr 2nd, 2020 Officially additional training dataset was released, then added unofficial copy here!",
      "votes": null
    },
    {
      "id": "802121",
      "postDate": "04/09/2020 06:40:37",
      "content": "<p>Thank you for the share.  Feels a bit lonely not having this competition on kaggle. \nStay safe and healthy ! </p>",
      "rawMarkdown": "Thank you for the share.  Feels a bit lonely not having this competition on kaggle. \nStay safe and healthy !",
      "votes": null
    },
    {
      "id": "802186",
      "postDate": "04/09/2020 08:00:59",
      "content": "<p>Me too, let's hope we could have it on Kaggle again next time.\nAnd wishing you to stay safe!</p>",
      "rawMarkdown": "Me too, let's hope we could have it on Kaggle again next time.\nAnd wishing you to stay safe!",
      "votes": null
    },
    {
      "id": "811738",
      "postDate": "04/18/2020 07:37:34",
      "content": "<p>Do you know why it's not posted here? I learned so much from the kernels and discussion here. I can't find anything close to that on their website. I was also looking forward to a lot of clean TF 2.x implementations! Regardless, I'm looking forward to what people come up with! </p>",
      "rawMarkdown": "Do you know why it's not posted here? I learned so much from the kernels and discussion here. I can't find anything close to that on their website. I was also looking forward to a lot of clean TF 2.x implementations! Regardless, I'm looking forward to what people come up with!",
      "votes": null
    },
    {
      "id": "813734",
      "postDate": "04/20/2020 00:08:50",
      "content": "<p>Hi, Austin. I'm not sure... I hope you can find ones you're looking for. I guess some would be released after competition finishes. Though it sounds like too late, but it'd be still helpful for learners/practitioners.</p>",
      "rawMarkdown": "Hi, Austin. I'm not sure... I hope you can find ones you're looking for. I guess some would be released after competition finishes. Though it sounds like too late, but it'd be still helpful for learners/practitioners.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 802121,
      "author_name": "nyleve",
      "author_url": "",
      "post_date": "04/09/2020 06:40:37",
      "content": "<p>Thank you for the share.  Feels a bit lonely not having this competition on kaggle. \nStay safe and healthy ! </p>",
      "votes": null,
      "replies": [
        {
          "id": 802186,
          "author_name": "daisukelab",
          "author_url": "",
          "post_date": "04/09/2020 08:00:59",
          "content": "<p>Me too, let's hope we could have it on Kaggle again next time.\nAnd wishing you to stay safe!</p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 811738,
          "author_name": "erosis",
          "author_url": "",
          "post_date": "04/18/2020 07:37:34",
          "content": "<p>Do you know why it's not posted here? I learned so much from the kernels and discussion here. I can't find anything close to that on their website. I was also looking forward to a lot of clean TF 2.x implementations! Regardless, I'm looking forward to what people come up with! </p>",
          "votes": null,
          "replies": []
        },
        {
          "id": 813734,
          "author_name": "daisukelab",
          "author_url": "",
          "post_date": "04/20/2020 00:08:50",
          "content": "<p>Hi, Austin. I'm not sure... I hope you can find ones you're looking for. I guess some would be released after competition finishes. Though it sounds like too late, but it'd be still helpful for learners/practitioners.</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "783639": "Dear all,\n\nFirst, I wish you are safe during this difficult time.\n\nAs I wrote in title, DCASE 2020 challenge is going on.\nUnfortunately no task is held in Kaggle this year,\nthen I'm sharing contents specifically prepared for task 2.\nThis time the task is Anomaly Detection (which I'm currently focusing on).\n\n## Datasets &amp; Notebooks\n- [DCASE 2020 Task 2 Unofficial Copy](https://www.kaggle.com/daisukelab/dc2020task2)\n    - [DCASE2020 Task2 Baseline AE Starter](https://www.kaggle.com/daisukelab/dcase2020-task2-baseline-ae-starter)\n    - [DCASE 2020 Task 2 EDA](https://www.kaggle.com/daisukelab/dcase-2020-task-2-eda)\n- [DCASE 2020 Task 2 Preprocessed (for CNN)](https://www.kaggle.com/daisukelab/dc2020task2prep)\n    - [DCASE2020 Task2 CNN-AE Starter](https://www.kaggle.com/daisukelab/dcase2020-task2-cnn-ae-starter)\n    - [DCASE 2020 Task 2 Preprocessed EDA](https://www.kaggle.com/daisukelab/dcase-2020-task-2-preprocessed-eda)\n- [DCASE 2020 Task 2 Additinal Set Unofficial Copy](https://www.kaggle.com/daisukelab/dc2020task2added) *NEW\n    - [DCASE 2020 Task 2 Additional Training Dataset EDA](https://www.kaggle.com/daisukelab/dcase-2020-task-2-additional-training-dataset-eda) *NEW\n\nYou can use these dataset copies and develop your solutions as same as Kaggle competitions.\nI wish you all keep safety, and may you have time to enjoy hacking datasets as usual...\n\n### UPDATE\n\n- Apr 2nd, 2020 Officially additional training dataset was released, then added unofficial copy here!",
    "802121": "Thank you for the share.  Feels a bit lonely not having this competition on kaggle. \nStay safe and healthy !",
    "802186": "Me too, let's hope we could have it on Kaggle again next time.\nAnd wishing you to stay safe!",
    "811738": "Do you know why it's not posted here? I learned so much from the kernels and discussion here. I can't find anything close to that on their website. I was also looking forward to a lot of clean TF 2.x implementations! Regardless, I'm looking forward to what people come up with!",
    "813734": "Hi, Austin. I'm not sure... I hope you can find ones you're looking for. I guess some would be released after competition finishes. Though it sounds like too late, but it'd be still helpful for learners/practitioners."
  },
  "source": "meta"
}