{
  "id": 468524,
  "title": "[Hot Tip 🔥] Reinforce Your Learning",
  "url": "/competitions/hms-harmful-brain-activity-classification/discussion/468524",
  "author_name": "",
  "post_date": "2024-01-17T00:19:47.406720700Z",
  "votes": 19,
  "comment_count": 1,
  "views": 0,
  "content": "<p>I couldn't help it with the pun in the title. There is no doubt (at least from my perspective) that Kaggle is hands down one of the best places to keep honing your craft when it comes to data and machine learning. The kaggle community is amazing with their sharing of knowledge. </p>\n<p>One recommendation that has helped me over the years, to help me nail down concepts is building notebooks from Kaggle competitions from scratch, after I have looked through them. If you are already committed to looking through the notebooks, might as well get the most you can out of them! Challenge yourself to try the same, struggle with the content, learn the in and outs of what is happening and you will find that you strongly understand the content 🗺️.</p>\n<p>Another added bonus, especially with regards to reconstructing the data used in the notebooks, is that you can also put yourself in a position to build better features / models with a deeper understanding.</p>\n<p>Hope this post is helps 🎉</p>",
  "messages": [
    {
      "id": "2605228",
      "postDate": "01/17/2024 00:19:47",
      "content": "<p>I couldn't help it with the pun in the title. There is no doubt (at least from my perspective) that Kaggle is hands down one of the best places to keep honing your craft when it comes to data and machine learning. The kaggle community is amazing with their sharing of knowledge. </p>\n<p>One recommendation that has helped me over the years, to help me nail down concepts is building notebooks from Kaggle competitions from scratch, after I have looked through them. If you are already committed to looking through the notebooks, might as well get the most you can out of them! Challenge yourself to try the same, struggle with the content, learn the in and outs of what is happening and you will find that you strongly understand the content 🗺️.</p>\n<p>Another added bonus, especially with regards to reconstructing the data used in the notebooks, is that you can also put yourself in a position to build better features / models with a deeper understanding.</p>\n<p>Hope this post is helps 🎉</p>",
      "rawMarkdown": "I couldn't help it with the pun in the title. There is no doubt (at least from my perspective) that Kaggle is hands down one of the best places to keep honing your craft when it comes to data and machine learning. The kaggle community is amazing with their sharing of knowledge. \n\nOne recommendation that has helped me over the years, to help me nail down concepts is building notebooks from Kaggle competitions from scratch, after I have looked through them. If you are already committed to looking through the notebooks, might as well get the most you can out of them! Challenge yourself to try the same, struggle with the content, learn the in and outs of what is happening and you will find that you strongly understand the content 🗺️.\n\nAnother added bonus, especially with regards to reconstructing the data used in the notebooks, is that you can also put yourself in a position to build better features / models with a deeper understanding.\n\nHope this post is helps 🎉",
      "votes": null
    },
    {
      "id": "2605277",
      "postDate": "01/17/2024 02:12:48",
      "content": "<p>I do this tip every time I see an interesting notebook. Totally agree.</p>",
      "rawMarkdown": "I do this tip every time I see an interesting notebook. Totally agree.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2605277,
      "author_name": "yantxx",
      "author_url": "",
      "post_date": "01/17/2024 02:12:48",
      "content": "<p>I do this tip every time I see an interesting notebook. Totally agree.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2605228": "I couldn't help it with the pun in the title. There is no doubt (at least from my perspective) that Kaggle is hands down one of the best places to keep honing your craft when it comes to data and machine learning. The kaggle community is amazing with their sharing of knowledge. \n\nOne recommendation that has helped me over the years, to help me nail down concepts is building notebooks from Kaggle competitions from scratch, after I have looked through them. If you are already committed to looking through the notebooks, might as well get the most you can out of them! Challenge yourself to try the same, struggle with the content, learn the in and outs of what is happening and you will find that you strongly understand the content 🗺️.\n\nAnother added bonus, especially with regards to reconstructing the data used in the notebooks, is that you can also put yourself in a position to build better features / models with a deeper understanding.\n\nHope this post is helps 🎉",
    "2605277": "I do this tip every time I see an interesting notebook. Totally agree."
  },
  "source": "meta"
}