{
  "fetched_at": "2026-10-24T12:40:41Z",
  "source_url": "https://www.kaggle.com/competitions/cifar10-cn/data",
  "pages": [
    {
      "name": "data-description",
      "content": "Use the \"cifar10_pca_template.ipynb\" notebook to download the dataset.",
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      "hasIsPublished": false,
      "postTitle": "",
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    {
      "name": "Description",
      "content": "The CIFAR-10 dataset consists of 60000 32x32 color images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.\nFor CifaCifar10 database -\nYou are given a readme file has a Template file to download the cifar10 dataset (it has a training and test dataset). You have to download the dataset using this.\n\nYour task is to Predict the correct class for every image in the test dataset.\n\nRead Instructions carefully -\n1. Submit a CSV file with only predictions for X test data. The file should not have any headers and should only have one column i.e. predictions.\n2. Predictions should be class names and not numbers.\n3. Your score is based on the number of accurate predictions.",
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      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Evaluation",
      "content": "The evaluation is based on Categorization. It will match the output and will find the accuracy.",
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      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
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    },
    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "mimeType": "",
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}