{
  "id": 419640,
  "title": "Comparing Various methods that I have tried out in this competition",
  "url": "/competitions/digit-recognizer/discussion/419640",
  "author_name": "Sai pavan",
  "post_date": "2023-06-26T22:25:48.087000",
  "votes": 3,
  "comment_count": 0,
  "views": null,
  "content": "<p>This dataset is very useful in trying out various algorithms and <br>\ntechniques. This competition has introduced me to image classification tasks!</p>\n<ul>\n<li>I have learnt <strong>data augmentation technique</strong> in this competition</li>\n<li>Also I have learnt to <strong>automate the process of comparing CV's</strong> of different classifiers.</li>\n<li>I have tried out the <strong>use cases with PCA</strong> on this dataset for the first time.</li>\n<li>I have also <strong>used Voting Classifier and GridSearchCV</strong> for the <br>\nfirst time , which surprised me the power of these tools.</li>\n</ul>\n<p>Just by comparing the results,<br>\nI got an accuracy score 97.7 after spending long hours of training my doubled training data with<br>\nData augmentation and GridSearchCV. Whereas, I was able to reach almost the same score 97.34% after just grouping some best classifers and using Voting classifier 😎😍      </p>\n<p><strong>Here are the notebooks:</strong></p>\n<p><strong>Digit recognizer with Data augmentation:</strong><br>\n<a href=\"https://www.kaggle.com/code/saipavankumaryedduri/digitrecognizer-using-knn-0-977-dataaugmentation?kernelSessionId=134415847\" target=\"_blank\">https://www.kaggle.com/code/saipavankumaryedduri/digitrecognizer-using-knn-0-977-dataaugmentation?kernelSessionId=134415847</a></p>\n<p><strong>Digit recognizer with Voting Classifier notebook:</strong><br>\n<a href=\"https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\" target=\"_blank\">https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978</a></p>\n<p><strong>Digit recognizer with PCA notebook:</strong><br>\n<a href=\"https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\" target=\"_blank\">https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978</a><br>\n<strong>Hope they help you</strong></p>\n<p>Cheers,</p>",
  "messages": [
    {
      "id": 2319128,
      "postDate": "2023-06-26T22:25:48.087Z",
      "content": "<p>This dataset is very useful in trying out various algorithms and <br>\ntechniques. This competition has introduced me to image classification tasks!</p>\n<ul>\n<li>I have learnt <strong>data augmentation technique</strong> in this competition</li>\n<li>Also I have learnt to <strong>automate the process of comparing CV's</strong> of different classifiers.</li>\n<li>I have tried out the <strong>use cases with PCA</strong> on this dataset for the first time.</li>\n<li>I have also <strong>used Voting Classifier and GridSearchCV</strong> for the <br>\nfirst time , which surprised me the power of these tools.</li>\n</ul>\n<p>Just by comparing the results,<br>\nI got an accuracy score 97.7 after spending long hours of training my doubled training data with<br>\nData augmentation and GridSearchCV. Whereas, I was able to reach almost the same score 97.34% after just grouping some best classifers and using Voting classifier 😎😍      </p>\n<p><strong>Here are the notebooks:</strong></p>\n<p><strong>Digit recognizer with Data augmentation:</strong><br>\n<a href=\"https://www.kaggle.com/code/saipavankumaryedduri/digitrecognizer-using-knn-0-977-dataaugmentation?kernelSessionId=134415847\" target=\"_blank\">https://www.kaggle.com/code/saipavankumaryedduri/digitrecognizer-using-knn-0-977-dataaugmentation?kernelSessionId=134415847</a></p>\n<p><strong>Digit recognizer with Voting Classifier notebook:</strong><br>\n<a href=\"https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\" target=\"_blank\">https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978</a></p>\n<p><strong>Digit recognizer with PCA notebook:</strong><br>\n<a href=\"https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\" target=\"_blank\">https://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978</a><br>\n<strong>Hope they help you</strong></p>\n<p>Cheers,</p>",
      "rawMarkdown": "This dataset is very useful in trying out various algorithms and \ntechniques. This competition has introduced me to image classification tasks!\n\n- I have learnt **data augmentation technique** in this competition\n- Also I have learnt to **automate the process of comparing CV's** of different classifiers.\n- I have tried out the **use cases with PCA** on this dataset for the first time.\n- I have also **used Voting Classifier and GridSearchCV** for the \nfirst time , which surprised me the power of these tools.\n\n\nJust by comparing the results,\nI got an accuracy score 97.7 after spending long hours of training my doubled training data with\nData augmentation and GridSearchCV. Whereas, I was able to reach almost the same score 97.34% after just grouping some best classifers and using Voting classifier 😎😍      \n\n**Here are the notebooks:**\n\n**Digit recognizer with Data augmentation:**\nhttps://www.kaggle.com/code/saipavankumaryedduri/digitrecognizer-using-knn-0-977-dataaugmentation?kernelSessionId=134415847\n\n**Digit recognizer with Voting Classifier notebook:**\nhttps://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\n\n**Digit recognizer with PCA notebook:**\nhttps://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\n**Hope they help you**\n\nCheers,",
      "votes": 3
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2319128": "This dataset is very useful in trying out various algorithms and \ntechniques. This competition has introduced me to image classification tasks!\n\n- I have learnt **data augmentation technique** in this competition\n- Also I have learnt to **automate the process of comparing CV's** of different classifiers.\n- I have tried out the **use cases with PCA** on this dataset for the first time.\n- I have also **used Voting Classifier and GridSearchCV** for the \nfirst time , which surprised me the power of these tools.\n\n\nJust by comparing the results,\nI got an accuracy score 97.7 after spending long hours of training my doubled training data with\nData augmentation and GridSearchCV. Whereas, I was able to reach almost the same score 97.34% after just grouping some best classifers and using Voting classifier 😎😍      \n\n**Here are the notebooks:**\n\n**Digit recognizer with Data augmentation:**\nhttps://www.kaggle.com/code/saipavankumaryedduri/digitrecognizer-using-knn-0-977-dataaugmentation?kernelSessionId=134415847\n\n**Digit recognizer with Voting Classifier notebook:**\nhttps://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\n\n**Digit recognizer with PCA notebook:**\nhttps://www.kaggle.com/code/saipavankumaryedduri/digit-recognizer-with-voting-classifier?kernelSessionId=134959978\n**Hope they help you**\n\nCheers,"
  }
}