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  "source_url": "https://www.kaggle.com/competitions/ai-110-1-hw1/data",
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      "content": "<ul>\n<li><strong>covid.train.csv</strong>> : Training data</li>\n<li><strong>covid.test.csv</strong> : Testing data</li>\n<li><strong>sampleSubmission.csv</strong> :  a sample submission file in the correct format</li>\n</ul>\n\n<h2>Description</h2>\n<ul>\n  <li>Given survey results in the <b>past 3 days</b> in a specific <b>state</b> in U.S., then\npredict the percentage of <b>new tested positive cases</b> in the 3rd day.</li>\n  <img src=\"https://img.onl/Lw3uJ3\" width=\"600\" height=\"100\" alt=\"Day3\">\n</ul>\n\n<h2>Data - Columns (Features) - Percentage%</h2>\n<ul>\n <li><b>States</b> (40, encoded to <b>one-hot</b> vectors)</li>\n <ul>\n <li>e.g. AL, AK, AZ, ... </li> \n <img src=\"https://img.onl/wWEoWa\" width=\"300\" height=\"50\" alt=\"One_hot\">\n </ul>\n <li><b>COVID-like illness</b> (4)</li>\n <ul>\n <li>e.g. cli,ili (influenza-like illness), ...</li>\n </ul>\n <li><b>Behavior Indicators</b> (8)</li>\n <ul>\n <li>e.g. wearing_mask, travel_outside_state, ...</li>\n </ul>\n <li><b>Mental Health Indicators</b> (5)</li>\n <ul>\n <li>e.g. anxious, depressed, ...</li>\n </ul>\n <li><b>Tested Positive Cases</b> (1)</li>\n <ul>\n <li><span style=\"color:red;\"><b>tested_positive</b> (this is what we want to predict).</span> </li>\n</ul>\n\n<img src=\"https://img.onl/BISEBN\" width=\"600\" height=\"150\" alt=\"Data\">",
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      "content": "<h2>Task Description</h2>\n<ul>\n  <li>COVID-19 daily cases prediction</li>\n  <li>Source: Delphi group @ CMU - A daily survey since April 2020 via\nfacebook.</li>\n  <img src=\"https://img.onl/50MbQz\" width=\"300\" height=\"50\" alt=\"percentage\">\n  <li>Training data: 2700 samples</li>\n  <li>Testing data: 893 samples</li>\n  <li>Evaluation metric: Root Mean Squared Error &lt; RMSE &gt;</li>\n  <img src=\"https://img.onl/jdgKIC\" width=\"400\" height=\"80\" alt=\"RMSE\">\n</ul>\n\n<h2>Objectives</h2>\n<ul>\n  <li>Solve a regression problem with deep neural networks (DNN)</li>\n  <li>Understand basic DNN training tips, e.g. hyper-parameter tuning, feature selection, regularization, ...</li>\n  <li>Get familiar with PyTorch.</li>\n</ul>\n\n<h2>Deadlines</h2>\n<ul>\n  <li>Kaggle: 110/07/10 23:59:59 </li>\n</ul>\n<b>No late submission!<p></p>\n\n<h2>Notes</h2>\n<ul>\n  <li>Team Name:  &lt; student ID &gt;_ &lt; anything &gt;（e.g. 1120530001_Daniel）</li>\n  <li>Compress your code and report into  &lt; student ID &gt; _hw1.zip;（e.g. 1120530001_hw1.zip）</li>\n  <li>Maximum Daily Submission: 5</li>\n</ul>\n</b>",
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      "name": "rules",
      "content": "This is the HW1 competition of AI_110.\n\n - You should finish your homework on your own.\n - You should not modify your prediction files manually.\n - Do not share codes or prediction files with any classmates.\n - Do not use any approaches to submit your results more than 6 times a day.\n - Do not search or use additional data or pre-trained models.\n",
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