{
  "fetched_at": "2026-10-19T14:28:01Z",
  "source_url": "https://www.kaggle.com/competitions/cs189-hw3-mnist-spring-2024/data",
  "pages": [
    {
      "name": "data-description",
      "content": "You will find a set of `.npz` files in the `data` folder for this homework. Each `.npz` file will load as a Python dictionary. Each dictionary contains three fields:\n- `training_data`, the training set features. Rows are sample points and columns are features.\n- `training_labels`, the training set labels. Rows are sample points. There is one column: the labels corresponding to rows of training_data above.\n- `test_data`, the test set features. Rows are sample points and columns are features. You will fit a model to predict the labels for this test set, and submit those predictions to Kaggle.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "The submitted predictions file should contain a header and have the following format:\n\n    Id,Category\n    1,0\n    2,0\n    3,0\n    ...\n    10000,1",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": "While discussion of homework problems is encouraged, all homeworks, including programming, must be written individually. We will actively check for plagiarism. The typical penalty is a large NEGATIVE score, but we reserve the right to give an instant F for even one violation, and will always give an F for two.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
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      "hasMimeType": false
    }
  ]
}