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 prior to that deadline.
\nHappy Modeling!
", "messages": [ { "id": 2255239, "postDate": "2023-05-11T15:37:49.040Z", "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 prior to that deadline.
\nHappy Modeling!
", "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 prior to that deadline.\n\n \n\nHappy Modeling!\n", "votes": 10 }, { "id": 2256113, "postDate": "2023-05-12T09:09:31.183Z", "content": "Thank You. It will be helpful for me. @maggiemd
", "rawMarkdown": "Thank You. It will be helpful for me. @maggiemd ", "votes": 1 }, { "id": 2257211, "postDate": "2023-05-13T06:23:38.223Z", "content": "happy kaggling, thnx for sharing
", "rawMarkdown": "happy kaggling, thnx for sharing", "votes": 2 }, { "id": 2256092, "postDate": "2023-05-12T08:58:28.620Z", "content": "Great advice for newcomers!
", "rawMarkdown": "Great advice for newcomers! ", "votes": 2 }, { "id": 2302081, "postDate": "2023-06-14T10:22:08.403Z", "content": "I particiate in competition for the first time. Please be kind to me.
", "rawMarkdown": "I particiate in competition for the first time. Please be kind to me." }, { "id": 2285651, "postDate": "2023-06-02T21:44:13.493Z", "content": "I like the competition model and withholding public notebooks in the final weeks to uphold the competitive spirit.
\nWhat's the first place someone new to Machine Learning should start to explore?
", "rawMarkdown": "I like the competition model and withholding public notebooks in the final weeks to uphold the competitive spirit. \n\nWhat's the first place someone new to Machine Learning should start to explore? " }, { "id": 2279745, "postDate": "2023-05-29T15:26:41.043Z", "content": "Thanks. the videos are really helpful for me.
", "rawMarkdown": "Thanks. the videos are really helpful for me." }, { "id": 2326872, "postDate": "2023-07-02T13:15:23.130Z", "content": "thanks for sharing
", "rawMarkdown": "thanks for sharing" }, { "id": 2316261, "postDate": "2023-06-24T18:24:36.763Z", "content": "Thanks a lot
", "rawMarkdown": "Thanks a lot" }, { "id": 2300221, "postDate": "2023-06-13T04:59:33.427Z", "content": "Thanks for the advice!
", "rawMarkdown": "Thanks for the advice!" } ], "comments": [ { "id": 2256113, "author_name": "Tamanna Akter Swarna", "author_url": "", "post_date": "2023-05-12T09:09:31.183000", "content": "Thank You. It will be helpful for me. @maggiemd
", "votes": 1, "replies": [] }, { "id": 2257211, "author_name": "Aisuluu Ulan kyzy", "author_url": "", "post_date": "2023-05-13T06:23:38.223000", "content": "happy kaggling, thnx for sharing
", "votes": 2, "replies": [] }, { "id": 2256092, "author_name": "Ericka42", "author_url": "", "post_date": "2023-05-12T08:58:28.620000", "content": "Great advice for newcomers!
", "votes": 2, "replies": [] }, { "id": 2302081, "author_name": "Gappy", "author_url": "", "post_date": "2023-06-14T10:22:08.403000", "content": "I particiate in competition for the first time. Please be kind to me.
", "votes": 0, "replies": [] }, { "id": 2285651, "author_name": "Oso Blanco", "author_url": "", "post_date": "2023-06-02T21:44:13.493000", "content": "I like the competition model and withholding public notebooks in the final weeks to uphold the competitive spirit.
\nWhat's the first place someone new to Machine Learning should start to explore?
", "votes": 0, "replies": [] }, { "id": 2279745, "author_name": "JIANKUN LUO", "author_url": "", "post_date": "2023-05-29T15:26:41.043000", "content": "Thanks. the videos are really helpful for me.
", "votes": 0, "replies": [] }, { "id": 2326872, "author_name": "huachi", "author_url": "", "post_date": "2023-07-02T13:15:23.130000", "content": "thanks for sharing
", "votes": 0, "replies": [] }, { "id": 2316261, "author_name": "tabaksezgin", "author_url": "", "post_date": "2023-06-24T18:24:36.763000", "content": "Thanks a lot
", "votes": 0, "replies": [] }, { "id": 2300221, "author_name": "Kelvin Lim", "author_url": "", "post_date": "2023-06-13T04:59:33.427000", "content": "Thanks for the advice!
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "2255239": "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 prior to that deadline.\n\n \n\nHappy Modeling!\n", "2256113": "Thank You. It will be helpful for me. @maggiemd ", "2257211": "happy kaggling, thnx for sharing", "2256092": "Great advice for newcomers! ", "2302081": "I particiate in competition for the first time. Please be kind to me.", "2285651": "I like the competition model and withholding public notebooks in the final weeks to uphold the competitive spirit. \n\nWhat's the first place someone new to Machine Learning should start to explore? ", "2279745": "Thanks. the videos are really helpful for me.", "2326872": "thanks for sharing", "2316261": "Thanks a lot", "2300221": "Thanks for the advice!" } }