{
  "fetched_at": "2026-10-19T17:13:46Z",
  "source_url": "https://www.kaggle.com/competitions/cse512springhw5/data",
  "pages": [
    {
      "name": "rules",
      "content": "\r\n\t<!-- Begin Base Rules -->\r\n    <h3>One account per participant</h3>\r\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\r\n    <h3>No private sharing outside teams</h3>\r\n    <p>\r\n        Privately sharing code or data outside of teams is not permitted.\r\n        It's okay to share code if made available to all participants on the forums.\r\n    </p>\r\n    <h3>Team Mergers</h3>\r\n    <p>Team mergers are not allowed in this competition.</p>\r\n\r\n    <h3>Team Limits</h3>\r\n    <p>There is no maximum team size.</p>\r\n    <h3>Submission Limits</h3>\r\n    <p>You may submit a maximum of 2 entries per day.</p>\r\n    <p>You may select up to 2 final submissions for judging.</p>\r\n    <h3>Competition Timeline</h3>\r\n    <p>Start Date: <strong>TBA</strong></p>\r\n    <p>Merger Deadline: <strong>None</strong></p>\r\n    <p>Entry Deadline: <strong>None</strong></p>\r\n    <p>End Date: <strong>2/1/2014 12:00 AM UTC</strong></p>\r\n\t<!-- End Base Rules -->\r\n<p>The rules page is a bit special: it will auto-update the text based on the parameters of the competition. The rules you need to add here are any additional rules relating to dataset usage. You may also put grading information here.</p>",
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    {
      "name": "data-description",
      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>train_data.h5</strong> - the training set</li>\n<li><strong>test_data.h5</strong> - the test set</li>\n<li><strong>train_label.h5</strong> - the training labels</li>\n<li><strong>val_data.h5</strong> - the validation data</li>\n<li><strong>val_label.h5</strong> - the validation labels</li>\n</ul>\n",
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    {
      "name": "Description",
      "content": "For human action recognition, you will be using skeleton data that encodes the 3D locations of 25 body joints. The data is collected by Kinect v2. There are 10 different action classes. There are 4000 training sequences, 800 validation sequences, and 1000 test sequences. Each sequence has 15 frames, each frame is a 75-dimension vector (the xyz positions of 25 joints). You will first train a LSTM for action classification. \n\nThen try to improve the network architecture and attach your results with the jupyter notebook. Also add the hyper-parameters explored. \n\nGLHF!",
      "isPublished": false,
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    }
  ]
}