{
  "fetched_at": "2026-10-24T16:22:52Z",
  "source_url": "https://www.kaggle.com/competitions/fall-2023-cisc6000-deep-learning-hw3/data",
  "pages": [
    {
      "name": "data-description",
      "content": "- Task One Image Genneration : celeba.zip\n\n- Task Two Language Modeling: anna.txt",
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      "postTitle": "",
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    {
      "name": "Description",
      "content": "VAE and RNN\n\n- In Kaggle:\n\n  Don't need to submit any CSV file\n\n  Download your latest version of all code in notebook format including Q2 and Q3\n\n- In Blackboard:\n\n  Submit your table 1 and table 2, some graphs, and some answers in a pdf file.\n\n  Submit your all code in notebook format including Q2 and Q3",
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      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
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    },
    {
      "name": "abstract",
      "content": "- Variational Autoencoder in Image Generation",
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      "hasIsPublished": false,
      "postTitle": "",
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      "mimeType": "",
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}