{
  "fetched_at": "2026-10-20T00:31:25Z",
  "source_url": "https://www.kaggle.com/competitions/ds36-whiskey-review-classification/data",
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    {
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      "content": "## Files\n\n*   **train.csv** - the training set\n*   **test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n*   **WhiskyFlavorDescriptors.csv** - supplemental information about the data\n\n## Data Dictionary\n- id - the review's unique identifier\n- description the review text itself\n- category the type of whiskey being reviewed\n\n",
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      "name": "Description",
      "content": "## Objective\nYour objective is to train a text classification model to analyze textual reviews of certain whiskeys in order to predict the type of whiskey being reviewed.\n\n## Background\nThe training dataset contains textual reviews of different kinds of whiskeys, and the category of whiskey being reviewed (1: Scotch, 2: Bourbon/Tennessee, 3: Craft, 4: Canadian).\n\nHowever the training dataset contains textual reviews, but no categories. So your job is to produce a solutions file that contains your model's predicted category for each of the reviews in the training set.\n\n## Data Dictionary\nThe competition data has been obtained from the Whiskey Advocate.\n\n## Files\n- train.csv - the training set\n- test.csv - the test set\n- sample_submission.csv - a sample submission file in the correct format\n\n## Columns\n- id: the review's unique identifier\n- description: the review text itself\n- category: the type of whiskey being reviewed (1: Scotch, 2: Bourbon/Tennessee, 3: Craft, 4: Canadian)",
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    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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