New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!
\nIf you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!
\nNew to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about site etiquette, or Kaggle lingo.
\nRemember: Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our Kaggle community guidelines.
\nA tip on sharing content - Kaggle is a collaborative community, whereby sharing techniques, starter notebooks, and ideas in the discussion forums are highly encouraged throughout the competition. However, as the competition draws closer to the final deadline it's customary to keep high-scoring notebooks withheld until after the competition has concluded. This maintains the spirit of the competition, while also allowing individuals to submit their own creative work without jeopardy of a higher-scoring notebook being available for an automatic higher rank (through copy/submit). We disable publishing of public notebooks within the final week of the competition, but encourage you to use your best judgment for time prior to that.
", "messages": [ { "id": "1731663", "postDate": "03/22/2022 15:28:19", "content": "New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!
\nIf you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!
\nNew to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about site etiquette, or Kaggle lingo.
\nRemember: Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our Kaggle community guidelines.
\nA tip on sharing content - Kaggle is a collaborative community, whereby sharing techniques, starter notebooks, and ideas in the discussion forums are highly encouraged throughout the competition. However, as the competition draws closer to the final deadline it's customary to keep high-scoring notebooks withheld until after the competition has concluded. This maintains the spirit of the competition, while also allowing individuals to submit their own creative work without jeopardy of a higher-scoring notebook being available for an automatic higher rank (through copy/submit). We disable publishing of public notebooks within the final week of the competition, but encourage you to use your best judgment for time prior to that.
", "rawMarkdown": "New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!\n\nIf you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!\n\nNew to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about [site etiquette](https://www.youtube.com/watch?v=aIus8si_Et0), or [Kaggle lingo](https://www.youtube.com/watch?v=sEJHyuWKd-s).\n\nRemember: Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our [Kaggle community guidelines](https://www.kaggle.com/community-guidelines).\n\nA tip on sharing content - Kaggle is a collaborative community, whereby sharing techniques, starter notebooks, and ideas in the discussion forums are highly encouraged throughout the competition. However, as the competition draws closer to the final deadline it's customary to keep high-scoring notebooks withheld until after the competition has concluded. This maintains the spirit of the competition, while also allowing individuals to submit their own creative work without jeopardy of a higher-scoring notebook being available for an automatic higher rank (through copy/submit). We disable publishing of public notebooks within the final week of the competition, but encourage you to use your best judgment for time prior to that.", "votes": null }, { "id": "1737245", "postDate": "03/28/2022 09:12:04", "content": "Got it! Thanks @maggiemd
", "rawMarkdown": "Got it! Thanks @maggiemd", "votes": null }, { "id": "1805211", "postDate": "05/29/2022 23:28:30", "content": "Looking forward to the results tomorrow & mostly the winner explanations afterwards
", "rawMarkdown": "Looking forward to the results tomorrow & mostly the winner explanations afterwards", "votes": null } ], "comments": [ { "id": 1737245, "author_name": "prosperalikizang", "author_url": "", "post_date": "03/28/2022 09:12:04", "content": "Got it! Thanks @maggiemd
", "votes": null, "replies": [] }, { "id": 1805211, "author_name": "suvash", "author_url": "", "post_date": "05/29/2022 23:28:30", "content": "Looking forward to the results tomorrow & mostly the winner explanations afterwards
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "1731663": "New to machine learning and data science? No question is too basic or too simple. Feel free to start your own thread, or use this thread as a place to post any first-timer clarifying questions for the Kaggle community to help you with!\n\nIf you would consider yourself a beginner but don't know where to get started, let other Kagglers help you take your first steps here!\n\nNew to Kaggle? Take a look at a few videos Dr. Rachael Tatman has put together to learn a bit more about [site etiquette](https://www.youtube.com/watch?v=aIus8si_Et0), or [Kaggle lingo](https://www.youtube.com/watch?v=sEJHyuWKd-s).\n\nRemember: Kaggle is for everyone. Whether you're teaming up or sharing tips in the competition forum, we expect everyone to follow our [Kaggle community guidelines](https://www.kaggle.com/community-guidelines).\n\nA tip on sharing content - Kaggle is a collaborative community, whereby sharing techniques, starter notebooks, and ideas in the discussion forums are highly encouraged throughout the competition. However, as the competition draws closer to the final deadline it's customary to keep high-scoring notebooks withheld until after the competition has concluded. This maintains the spirit of the competition, while also allowing individuals to submit their own creative work without jeopardy of a higher-scoring notebook being available for an automatic higher rank (through copy/submit). We disable publishing of public notebooks within the final week of the competition, but encourage you to use your best judgment for time prior to that.", "1737245": "Got it! Thanks @maggiemd", "1805211": "Looking forward to the results tomorrow & mostly the winner explanations afterwards" }, "source": "meta" }