{
  "id": 416650,
  "title": "Easy-Peasy CNN Tutorial for Beginners",
  "url": "/competitions/digit-recognizer/discussion/416650",
  "author_name": "Akshit Sharma",
  "post_date": "2023-06-12T13:54:58.630000",
  "votes": 2,
  "comment_count": 1,
  "views": null,
  "content": "<p>Hello everyone!</p>\n<p>I am excited to share my latest Kaggle notebook with you all. The main point of creating this notebook was to explain implementation of a CNN architecture for the Digit Recognizer competition in an easy way (thereby allowing this notebook to serve as a tutorial for beginners).I have tried my best to elaborate the complete code wherever possible with instructions + illustrations</p>\n<p>I would love to hear your feedback and thoughts on my notebook, so please do feel free to comment and share your views. In case you do find this notebook helpful, please do not hesitate to give it an upvote or share it </p>\n<p>Link: <a href=\"https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners\" target=\"_blank\">https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners</a></p>\n<p>Thanks a lot for your time and support :)<br>\nAkshit</p>",
  "messages": [
    {
      "id": 2297312,
      "postDate": "2023-06-12T13:54:58.630Z",
      "content": "<p>Hello everyone!</p>\n<p>I am excited to share my latest Kaggle notebook with you all. The main point of creating this notebook was to explain implementation of a CNN architecture for the Digit Recognizer competition in an easy way (thereby allowing this notebook to serve as a tutorial for beginners).I have tried my best to elaborate the complete code wherever possible with instructions + illustrations</p>\n<p>I would love to hear your feedback and thoughts on my notebook, so please do feel free to comment and share your views. In case you do find this notebook helpful, please do not hesitate to give it an upvote or share it </p>\n<p>Link: <a href=\"https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners\" target=\"_blank\">https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners</a></p>\n<p>Thanks a lot for your time and support :)<br>\nAkshit</p>",
      "rawMarkdown": "Hello everyone!\n\nI am excited to share my latest Kaggle notebook with you all. The main point of creating this notebook was to explain implementation of a CNN architecture for the Digit Recognizer competition in an easy way (thereby allowing this notebook to serve as a tutorial for beginners).I have tried my best to elaborate the complete code wherever possible with instructions + illustrations\n\nI would love to hear your feedback and thoughts on my notebook, so please do feel free to comment and share your views. In case you do find this notebook helpful, please do not hesitate to give it an upvote or share it \n\nLink: [https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners](https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners)\n\nThanks a lot for your time and support :)\nAkshit\n\n\n",
      "votes": 2
    },
    {
      "id": 2316547,
      "postDate": "2023-06-25T04:35:40.297Z",
      "content": "<p>What accuracy does this give?</p>",
      "rawMarkdown": "What accuracy does this give?"
    }
  ],
  "comments": [
    {
      "id": 2316547,
      "author_name": "Finny Cairns",
      "author_url": "",
      "post_date": "2023-06-25T04:35:40.297000",
      "content": "<p>What accuracy does this give?</p>",
      "votes": 0,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2297312": "Hello everyone!\n\nI am excited to share my latest Kaggle notebook with you all. The main point of creating this notebook was to explain implementation of a CNN architecture for the Digit Recognizer competition in an easy way (thereby allowing this notebook to serve as a tutorial for beginners).I have tried my best to elaborate the complete code wherever possible with instructions + illustrations\n\nI would love to hear your feedback and thoughts on my notebook, so please do feel free to comment and share your views. In case you do find this notebook helpful, please do not hesitate to give it an upvote or share it \n\nLink: [https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners](https://www.kaggle.com/code/akshitsharma1/easy-peasy-detailed-cnn-tutorial-for-beginners)\n\nThanks a lot for your time and support :)\nAkshit\n\n\n",
    "2316547": "What accuracy does this give?"
  }
}