{
  "fetched_at": "2026-10-20T10:49:32Z",
  "source_url": "https://www.kaggle.com/competitions/first-1/data",
  "pages": [
    {
      "name": "rules",
      "content": "Have fun!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "data-description",
      "content": "## All of the data is located within the Colab instance, but you can also download it here if needed. \n\nmpg_train_dataset: X and Y train data for NN\n\nmpg_test_X: test data in order to generate predictions for submission",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "# Welcome to the 1st challenge of the FIRST AI CrashCourse! \n\n## We'll be trying to predict the fuel efficiency of a car, using a variety of factors as the inputs, and a Deep Neural Network to process the data.\n\nFollow along with the [Github][1] and submit your NN predictions by clicking up above and uploading the submission.csv file.\n\n\n  [1]: https://github.com/QuantumTCode/FIRST-AI-Crash-Course/tree/master/Lesson%20%231:%20Deep%20Neural%20Networks",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "### The evaluation metric for this competition is Root Mean-Squared Error (RMSE).",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}