{
  "id": 665089,
  "title": "Beginner here — Need guidance on how to start this competition properly",
  "url": "/competitions/csiro-biomass/discussion/665089",
  "author_name": "",
  "post_date": "2025-12-30T03:35:04.144940100Z",
  "votes": 1,
  "comment_count": 2,
  "views": 0,
  "content": "<p>Hello everyone,</p>\n<p>I’m a beginner in machine learning and this is my first time participating in a Kaggle competition.\nTo be honest, I’m feeling a bit overwhelmed and confused about where to start.</p>\n<p>I have joined this competition, but I’m not fully sure:</p>\n<p>How to understand the problem statement deeply</p>\n<p>How to explore the dataset correctly</p>\n<p>What kind of baseline model I should start with</p>\n<p>Which skills or concepts I should focus on learning to compete better</p>\n<p>I really want to learn properly, not just submit random code.\nIf anyone could suggest:</p>\n<p>A simple step-by-step approach for beginners</p>\n<p>Useful notebooks, tutorials, or learning resources related to this competition</p>\n<p>Common mistakes beginners should avoid</p>\n<p>I would be very grateful.\nAny advice, even small tips, would help me a lot </p>\n<p>Thank you for your time and support!</p>",
  "messages": [
    {
      "id": "3383408",
      "postDate": "12/30/2025 03:35:04",
      "content": "<p>Hello everyone,</p>\n<p>I’m a beginner in machine learning and this is my first time participating in a Kaggle competition.\nTo be honest, I’m feeling a bit overwhelmed and confused about where to start.</p>\n<p>I have joined this competition, but I’m not fully sure:</p>\n<p>How to understand the problem statement deeply</p>\n<p>How to explore the dataset correctly</p>\n<p>What kind of baseline model I should start with</p>\n<p>Which skills or concepts I should focus on learning to compete better</p>\n<p>I really want to learn properly, not just submit random code.\nIf anyone could suggest:</p>\n<p>A simple step-by-step approach for beginners</p>\n<p>Useful notebooks, tutorials, or learning resources related to this competition</p>\n<p>Common mistakes beginners should avoid</p>\n<p>I would be very grateful.\nAny advice, even small tips, would help me a lot </p>\n<p>Thank you for your time and support!</p>",
      "rawMarkdown": "Hello everyone,\n\nI’m a beginner in machine learning and this is my first time participating in a Kaggle competition.\nTo be honest, I’m feeling a bit overwhelmed and confused about where to start.\n\nI have joined this competition, but I’m not fully sure:\n\nHow to understand the problem statement deeply\n\nHow to explore the dataset correctly\n\nWhat kind of baseline model I should start with\n\nWhich skills or concepts I should focus on learning to compete better\n\nI really want to learn properly, not just submit random code.\nIf anyone could suggest:\n\nA simple step-by-step approach for beginners\n\nUseful notebooks, tutorials, or learning resources related to this competition\n\nCommon mistakes beginners should avoid\n\nI would be very grateful.\nAny advice, even small tips, would help me a lot \n\nThank you for your time and support!",
      "votes": null
    },
    {
      "id": "3383412",
      "postDate": "12/30/2025 04:07:31",
      "content": "<p>Start by reading every discussion post.<br>\nLook over the top notebooks with EDA in the title.</p>\n<p>Look over the top dozen or more of shared notebooks - by votes  - than by score.</p>\n<p>Pick a notebook that matches your skill, your preferred layout, what seems readable to you.  Fork it.</p>\n<p>If you can afford it - buy this book.\n<strong>The Kaggle Book: Master data science competitions with machine learning, GenAI, and LLMs</strong></p>\n<p>Start a competition with all 3 months to go - you pretty late for this one :)</p>",
      "rawMarkdown": "Start by reading every discussion post.   \nLook over the top notebooks with EDA in the title.\n\nLook over the top dozen or more of shared notebooks - by votes  - than by score.\n\nPick a notebook that matches your skill, your preferred layout, what seems readable to you.  Fork it.\n\nIf you can afford it - buy this book.\n**The Kaggle Book: Master data science competitions with machine learning, GenAI, and LLMs**\n\nStart a competition with all 3 months to go - you pretty late for this one :)",
      "votes": null
    },
    {
      "id": "3383495",
      "postDate": "12/30/2025 09:34:47",
      "content": "<p>thank you</p>",
      "rawMarkdown": "thank you",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 3383412,
      "author_name": "pcjimmmy",
      "author_url": "",
      "post_date": "12/30/2025 04:07:31",
      "content": "<p>Start by reading every discussion post.<br>\nLook over the top notebooks with EDA in the title.</p>\n<p>Look over the top dozen or more of shared notebooks - by votes  - than by score.</p>\n<p>Pick a notebook that matches your skill, your preferred layout, what seems readable to you.  Fork it.</p>\n<p>If you can afford it - buy this book.\n<strong>The Kaggle Book: Master data science competitions with machine learning, GenAI, and LLMs</strong></p>\n<p>Start a competition with all 3 months to go - you pretty late for this one :)</p>",
      "votes": null,
      "replies": [
        {
          "id": 3383495,
          "author_name": "rubel01",
          "author_url": "",
          "post_date": "12/30/2025 09:34:47",
          "content": "<p>thank you</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "3383408": "Hello everyone,\n\nI’m a beginner in machine learning and this is my first time participating in a Kaggle competition.\nTo be honest, I’m feeling a bit overwhelmed and confused about where to start.\n\nI have joined this competition, but I’m not fully sure:\n\nHow to understand the problem statement deeply\n\nHow to explore the dataset correctly\n\nWhat kind of baseline model I should start with\n\nWhich skills or concepts I should focus on learning to compete better\n\nI really want to learn properly, not just submit random code.\nIf anyone could suggest:\n\nA simple step-by-step approach for beginners\n\nUseful notebooks, tutorials, or learning resources related to this competition\n\nCommon mistakes beginners should avoid\n\nI would be very grateful.\nAny advice, even small tips, would help me a lot \n\nThank you for your time and support!",
    "3383412": "Start by reading every discussion post.   \nLook over the top notebooks with EDA in the title.\n\nLook over the top dozen or more of shared notebooks - by votes  - than by score.\n\nPick a notebook that matches your skill, your preferred layout, what seems readable to you.  Fork it.\n\nIf you can afford it - buy this book.\n**The Kaggle Book: Master data science competitions with machine learning, GenAI, and LLMs**\n\nStart a competition with all 3 months to go - you pretty late for this one :)",
    "3383495": "thank you"
  },
  "source": "meta"
}