{
  "fetched_at": "2026-10-20T08:45:37Z",
  "source_url": "https://www.kaggle.com/competitions/deeplearningclassificationtask/data",
  "pages": [
    {
      "name": "data-description",
      "content": "# Download Dataset from : https://drive.google.com/file/d/1fWthkxdN-scIJd5KUmo7oYax-ecDk859/view?usp=sharing\n# DATASET\n- Training set: 5,000 images\n- Test set: 8,000 images\n- Image size: 96x96\n\n# Label details\nLabel in training data consists of 10 labels from 0 to 9 and the details below.\n\n- 0 airplane\n- 1 bird\n- 2 car\n- 3 cat\n- 4 deer\n- 5 dog\n- 6 horse\n- 7 monkey\n- 8 ship\n- 9 truck",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "##  Description\n- The goal is to achieve high accuracy on a given dataset.\n- You can use any network and any training tricks.\n- You can use pre-trained models\n- To prevent using extensive GPU resources, you should use a network that can be trained by using the resources provided by Google Colab (Other resources are strictly not allowed).\n- Please set your team name  as your name,  shown in your CV.\n- For any queries, you can post them on the [discussion Section](https://www.kaggle.com/c/deeplearningclassificationtask/discussion)\n\nFor guidance and sample code, you can download [this ipynb file](https://drive.google.com/file/d/1nJNZ61ZgQPswTarB5J7PgyimB8e_DP_s/view?usp=sharing), upload it on your google colab ([How to upload ipynb file on google colab](https://www.youtube.com/watch?v=uEFsQkhrAOA)) and everything is mentioned in the file. If you face any issue, post question in [discussion](https://www.kaggle.com/c/deeplearningclassificationtask/discussion) or just send an email to teerathkumar@khu.ac.kr\n\nDon't forget to read the [FAQs section](https://www.kaggle.com/c/deeplearningclassificationtask/overview/faqs). \n\n**Note: There are 10 submissions per day.**",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "# Objective\nThe network predicts which class a given image corresponds to. (0~9)\n\n# Performance evaluation indicator\nThe evaluation indicator is the accuracy of comparing the predicted by the model to the actual label.\n\n# Submission file format\nSubmitted files must be submitted as .csv files, and the results for 8000 images must be listed in order.\nThe .csv file has a total of 2 columns.\n\n# Id: ID of the image\nCategory: Label from 0 to 9\nId,  Category\n0,     9\n1,      7\n2,     3\n3,     8\nEtc.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "FAQs",
      "content": "- **How much time I am allowed for Kaggle based tasks (part-1), and when I am supposed to start working?**\nResponse:It is going to end on 09/13/2021 11:59 PM KST, So you must make your final submission before that. You can start working now. \n\n\n- **When will part-2 of the coding interview be, and What will it be about?**\nResponse: After 09/13/2021 11:59 PM KST, based on the final leaderboard result, you will be invited for an interview. It will be about your solution, that how you achieve performance, which technique you used etc. \n\n- **Will coding interview be on the same day of theoretical test?**\nResponse: No, Coding interview will be conducted after your final submission on Kaggle.\n\n- **When should I start coding?**\nResponse: As soon as possible, you can. \n\n\n\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}