{
  "fetched_at": "2026-10-19T07:38:05Z",
  "source_url": "https://www.kaggle.com/competitions/aida-434-image-data/data",
  "pages": [
    {
      "name": "data-description",
      "content": "<h2>File descriptions</h2>\n<ul>\n<li><strong>training</strong> - the training set</li>\n<li><strong>testing</strong> - the test set</li>\n<li><strong>validation</strong> - the validation set</li>\n<li><strong>sample.csv</strong> - a sample submission file in the correct format</li>\n</ul>",
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    {
      "name": "Description",
      "content": "<p>In this homework, we will train a model for classifying image. This dataset includes eleven image classes, and there are training and validation dataset. We will evaluate your model with testing dataset.</p>\n<p>You are free to use any neural network structure, any DL libary like TF, Keras, Pytorch, or any language like C, Java, Javascript, Python.</p>\n<p>Please register a Kaggle account with your student ID.</p>\n<h2>Output format</h2>\n<p>A submission file of prediction results should be a CSV file containing two columns: Id and Label, separated by ','.</p>\n<p>The file should contain a header and have the following format:</p>\n\n<pre>| ID | label |\n| 0.jpg| Bread |\n| 1.jpg| Bread |\n| 2.jpg| Bread |\n</pre>\n\n<img src=\"https://scontent.ftpe8-4.fna.fbcdn.net/v/t1.6435-9/217439570_1629338330595693_1411903995132207357_n.jpg?_nc_cat=110&amp;ccb=1-3&amp;_nc_sid=730e14&amp;_nc_ohc=IyT8gitK9GYAX_cDR1O&amp;_nc_oc=AQn8PszgnpyWzeFQnyEgMNX1EroGmtpNOjhjQkBuTbJbcSDiA_ct7AeWT32PrXrPQXo&amp;_nc_ht=scontent.ftpe8-4.fna&amp;oh=1f6f433f9b30dc34224b602176ea0da0&amp;oe=60FDD60E\">",
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    {
      "name": "Evaluation",
      "content": "\n<p>The evaluation metric for this competition is Accuracy. </p>",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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