{
  "id": 379612,
  "title": "Webinar on the competition - 20 January 17.00 Paris time ",
  "url": "/competitions/g2net-detecting-continuous-gravitational-waves/discussion/379612",
  "author_name": "Alexander Chervov",
  "post_date": "2023-01-20T10:37:33.638000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p>We will organize a webinar to discuss the competition - everybody welcome.<br>\nZoom link will be available at <a href=\"https://t.me/sberlogabig\" target=\"_blank\">https://t.me/sberlogabig</a> shortly before the start.<br>\nVideo records of the talks: <a href=\"https://www.youtube.com/c/SciBerloga\" target=\"_blank\">https://www.youtube.com/c/SciBerloga</a> - subscribe our channel !</p>\n<p>🚀 <a href=\"https://www.kaggle.com/SBERLOGACOMPETE\" target=\"_blank\">@SBERLOGACOMPETE</a> webinar on  data science:<br>\n👨‍🔬 Dmitrii Rudenko \"G2 Gravitational waves Kaggle competition debrief\" <br>\n⌚️ 20 January, Friday, 17.00  (Paris Time)</p>\n<p><a target=\"_blank\">Add to Google Calendar</a>)</p>\n<p>Welcome to the G2 Kaggle competition debrief on Detecting Gravitational Waves! My name is Dmitrii Rudenko and I am excited to share with you the top solutions from this competition, as well as my own bronze medal-winning solution. As many of you may know, the task in this competition was to use computer vision techniques to detect gravitational waves in images. These waves are extremely faint and difficult to detect, making this a challenging problem for machine learning algorithms. However, through the use of innovative techniques and careful tuning of models, we were able to achieve impressive results. I look forward to discussing the details of these solutions with you and hearing your thoughts and insights on the topic. Let's get started!</p>\n<p>Link to the competition: <a href=\"https://www.kaggle.com/competitions/g2net-detecting-continuous-gravitational-waves/overview\" target=\"_blank\">https://www.kaggle.com/competitions/g2net-detecting-continuous-gravitational-waves/overview</a></p>\n<p>Zoom link will be available at <br>\n<a href=\"https://t.me/sberlogabig\" target=\"_blank\">https://t.me/sberlogabig</a> shortly before the start.</p>\n<p>Video records of the talks: <a href=\"https://www.youtube.com/c/SciBerloga\" target=\"_blank\">https://www.youtube.com/c/SciBerloga</a> - subscribe our channel !</p>",
  "messages": [
    {
      "id": 2108195,
      "postDate": "2023-01-20T10:37:33.640Z",
      "content": "<p>We will organize a webinar to discuss the competition - everybody welcome.<br>\nZoom link will be available at <a href=\"https://t.me/sberlogabig\" target=\"_blank\">https://t.me/sberlogabig</a> shortly before the start.<br>\nVideo records of the talks: <a href=\"https://www.youtube.com/c/SciBerloga\" target=\"_blank\">https://www.youtube.com/c/SciBerloga</a> - subscribe our channel !</p>\n<p>🚀 <a href=\"https://www.kaggle.com/SBERLOGACOMPETE\" target=\"_blank\">@SBERLOGACOMPETE</a> webinar on  data science:<br>\n👨‍🔬 Dmitrii Rudenko \"G2 Gravitational waves Kaggle competition debrief\" <br>\n⌚️ 20 January, Friday, 17.00  (Paris Time)</p>\n<p><a target=\"_blank\">Add to Google Calendar</a>)</p>\n<p>Welcome to the G2 Kaggle competition debrief on Detecting Gravitational Waves! My name is Dmitrii Rudenko and I am excited to share with you the top solutions from this competition, as well as my own bronze medal-winning solution. As many of you may know, the task in this competition was to use computer vision techniques to detect gravitational waves in images. These waves are extremely faint and difficult to detect, making this a challenging problem for machine learning algorithms. However, through the use of innovative techniques and careful tuning of models, we were able to achieve impressive results. I look forward to discussing the details of these solutions with you and hearing your thoughts and insights on the topic. Let's get started!</p>\n<p>Link to the competition: <a href=\"https://www.kaggle.com/competitions/g2net-detecting-continuous-gravitational-waves/overview\" target=\"_blank\">https://www.kaggle.com/competitions/g2net-detecting-continuous-gravitational-waves/overview</a></p>\n<p>Zoom link will be available at <br>\n<a href=\"https://t.me/sberlogabig\" target=\"_blank\">https://t.me/sberlogabig</a> shortly before the start.</p>\n<p>Video records of the talks: <a href=\"https://www.youtube.com/c/SciBerloga\" target=\"_blank\">https://www.youtube.com/c/SciBerloga</a> - subscribe our channel !</p>",
      "rawMarkdown": "We will organize a webinar to discuss the competition - everybody welcome.\nZoom link will be available at https://t.me/sberlogabig shortly before the start.\nVideo records of the talks: https://www.youtube.com/c/SciBerloga - subscribe our channel !\n\n\n🚀 @SBERLOGACOMPETE webinar on  data science:\n👨‍🔬 Dmitrii Rudenko \"G2 Gravitational waves Kaggle competition debrief\" \n⌚️ 20 January, Friday, 17.00  (Paris Time)\n\n[Add to Google Calendar]( (https://calendar.google.com/calendar/render?action=TEMPLATE&dates=20230120T160000Z%2F20230120T183000Z&details=Zoom%20link%20will%20be%20available%20at%20%0Ahttps%3A%2F%2Ft.me%2Fsberlogabig%20shortly%20before%20the%20start.&text=%20%40SBERLOGABIG%20%20Dmitrii%20Rudenko%20%22G2%20Gravitational%20waves%20Kaggle%20competition%20debrief%22))\n\n\nWelcome to the G2 Kaggle competition debrief on Detecting Gravitational Waves! My name is Dmitrii Rudenko and I am excited to share with you the top solutions from this competition, as well as my own bronze medal-winning solution. As many of you may know, the task in this competition was to use computer vision techniques to detect gravitational waves in images. These waves are extremely faint and difficult to detect, making this a challenging problem for machine learning algorithms. However, through the use of innovative techniques and careful tuning of models, we were able to achieve impressive results. I look forward to discussing the details of these solutions with you and hearing your thoughts and insights on the topic. Let's get started!\n\nLink to the competition: https://www.kaggle.com/competitions/g2net-detecting-continuous-gravitational-waves/overview\n\nZoom link will be available at \nhttps://t.me/sberlogabig shortly before the start.\n\nVideo records of the talks: https://www.youtube.com/c/SciBerloga - subscribe our channel !\n",
      "votes": 1
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2108195": "We will organize a webinar to discuss the competition - everybody welcome.\nZoom link will be available at https://t.me/sberlogabig shortly before the start.\nVideo records of the talks: https://www.youtube.com/c/SciBerloga - subscribe our channel !\n\n\n🚀 @SBERLOGACOMPETE webinar on  data science:\n👨‍🔬 Dmitrii Rudenko \"G2 Gravitational waves Kaggle competition debrief\" \n⌚️ 20 January, Friday, 17.00  (Paris Time)\n\n[Add to Google Calendar]( (https://calendar.google.com/calendar/render?action=TEMPLATE&dates=20230120T160000Z%2F20230120T183000Z&details=Zoom%20link%20will%20be%20available%20at%20%0Ahttps%3A%2F%2Ft.me%2Fsberlogabig%20shortly%20before%20the%20start.&text=%20%40SBERLOGABIG%20%20Dmitrii%20Rudenko%20%22G2%20Gravitational%20waves%20Kaggle%20competition%20debrief%22))\n\n\nWelcome to the G2 Kaggle competition debrief on Detecting Gravitational Waves! My name is Dmitrii Rudenko and I am excited to share with you the top solutions from this competition, as well as my own bronze medal-winning solution. As many of you may know, the task in this competition was to use computer vision techniques to detect gravitational waves in images. These waves are extremely faint and difficult to detect, making this a challenging problem for machine learning algorithms. However, through the use of innovative techniques and careful tuning of models, we were able to achieve impressive results. I look forward to discussing the details of these solutions with you and hearing your thoughts and insights on the topic. Let's get started!\n\nLink to the competition: https://www.kaggle.com/competitions/g2net-detecting-continuous-gravitational-waves/overview\n\nZoom link will be available at \nhttps://t.me/sberlogabig shortly before the start.\n\nVideo records of the talks: https://www.youtube.com/c/SciBerloga - subscribe our channel !\n"
  }
}