{
  "id": 319194,
  "title": "MNIST – Getting start with CV with PyTorch F1_0.99",
  "url": "/competitions/digit-recognizer/discussion/319194",
  "author_name": "Ahmed",
  "post_date": "2022-04-15T21:05:06.254000",
  "votes": 1,
  "comment_count": 2,
  "views": null,
  "content": "<p>I'm very pleased to share with you my latest tutorials on how to start with Computer vision by applying deep learning to the MNIST dataset.</p>\n<p>This tutorial aims to help beginner and intermediate machine learning engineering combine their proficiencies with <strong>python</strong>, <strong>mathematics</strong> with  <strong>PyTorch</strong> for having dense, high accuracy algorithms to solve a simple problem like MNIST. </p>\n<p>MNIST dataset considers being the open door for having an understanding of computer vision, so spend time on it to understand how you can play with images in the future.</p>\n<p>I hope you like the Kernel, please don't forget to leave your opinion since I would like to know about what you are working on, too!</p>\n<p>Kernel: <a href=\"https://www.kaggle.com/code/dsxavier/mnist-getting-start-with-cv-with-pytorch-f1-0-99/notebook\" target=\"_blank\">MNIST – Getting start with CV with PyTorch F1_0.99</a></p>",
  "messages": [
    {
      "id": 1771037,
      "postDate": "2022-04-28T21:06:26.290Z",
      "content": "<p>Thanks for sharing!</p>",
      "rawMarkdown": "Thanks for sharing!",
      "votes": 1,
      "replies": [
        {
          "id": 1771068,
          "postDate": "2022-04-28T21:28:11.260Z",
          "content": "<p>Happy to help!</p>",
          "rawMarkdown": "Happy to help!"
        }
      ]
    },
    {
      "id": 1756779,
      "postDate": "2022-04-15T21:05:06.253Z",
      "content": "<p>I'm very pleased to share with you my latest tutorials on how to start with Computer vision by applying deep learning to the MNIST dataset.</p>\n<p>This tutorial aims to help beginner and intermediate machine learning engineering combine their proficiencies with <strong>python</strong>, <strong>mathematics</strong> with  <strong>PyTorch</strong> for having dense, high accuracy algorithms to solve a simple problem like MNIST. </p>\n<p>MNIST dataset considers being the open door for having an understanding of computer vision, so spend time on it to understand how you can play with images in the future.</p>\n<p>I hope you like the Kernel, please don't forget to leave your opinion since I would like to know about what you are working on, too!</p>\n<p>Kernel: <a href=\"https://www.kaggle.com/code/dsxavier/mnist-getting-start-with-cv-with-pytorch-f1-0-99/notebook\" target=\"_blank\">MNIST – Getting start with CV with PyTorch F1_0.99</a></p>",
      "rawMarkdown": "I'm very pleased to share with you my latest tutorials on how to start with Computer vision by applying deep learning to the MNIST dataset.\n\nThis tutorial aims to help beginner and intermediate machine learning engineering combine their proficiencies with **python**, **mathematics** with  **PyTorch** for having dense, high accuracy algorithms to solve a simple problem like MNIST. \n\nMNIST dataset considers being the open door for having an understanding of computer vision, so spend time on it to understand how you can play with images in the future.\n\nI hope you like the Kernel, please don't forget to leave your opinion since I would like to know about what you are working on, too!\n\nKernel: [MNIST – Getting start with CV with PyTorch F1_0.99](https://www.kaggle.com/code/dsxavier/mnist-getting-start-with-cv-with-pytorch-f1-0-99/notebook)",
      "votes": 1
    }
  ],
  "comments": [
    {
      "id": 1771037,
      "author_name": "Kuangen Zhang",
      "author_url": "",
      "post_date": "2022-04-28T21:06:26.290000",
      "content": "<p>Thanks for sharing!</p>",
      "votes": 1,
      "replies": [
        {
          "id": 1771068,
          "author_name": "Ahmed",
          "author_url": "",
          "post_date": "2022-04-28T21:28:11.260000",
          "content": "<p>Happy to help!</p>",
          "votes": 0,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "1771037": "Thanks for sharing!",
    "1756779": "I'm very pleased to share with you my latest tutorials on how to start with Computer vision by applying deep learning to the MNIST dataset.\n\nThis tutorial aims to help beginner and intermediate machine learning engineering combine their proficiencies with **python**, **mathematics** with  **PyTorch** for having dense, high accuracy algorithms to solve a simple problem like MNIST. \n\nMNIST dataset considers being the open door for having an understanding of computer vision, so spend time on it to understand how you can play with images in the future.\n\nI hope you like the Kernel, please don't forget to leave your opinion since I would like to know about what you are working on, too!\n\nKernel: [MNIST – Getting start with CV with PyTorch F1_0.99](https://www.kaggle.com/code/dsxavier/mnist-getting-start-with-cv-with-pytorch-f1-0-99/notebook)"
  }
}