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": "2172700", "postDate": "03/07/2023 18:04:36", "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!", "votes": null }, { "id": "2174124", "postDate": "03/08/2023 21:20:30", "content": "Hi. I am new to Kaggle. I can see that the competition has a code tab where people are uploading their codes. So, how it works? Why they are sharing their codes before the competition ends?
", "rawMarkdown": "Hi. I am new to Kaggle. I can see that the competition has a code tab where people are uploading their codes. So, how it works? Why they are sharing their codes before the competition ends?", "votes": null }, { "id": "2178047", "postDate": "03/12/2023 03:41:52", "content": "👍👍👍👍👍
", "rawMarkdown": "👍👍👍👍👍", "votes": null }, { "id": "2181421", "postDate": "03/14/2023 14:10:18", "content": "Hey Reza,
\nI'm new also in kaggle, and I find that practice is good to share knowledge between us.
\nanother point : if you read how kaggle handle ranking, you can understand also that is not about winning the first place but we can earn medals. and then you can not only earn medals in the competition but also medals related to your notebook and your discussions with other members. and if I'm not wrong you can share a version and keep working and optimizing your work in another version without sharing it.
Thanks for your information
", "rawMarkdown": "Thanks for your information", "votes": null }, { "id": "2185582", "postDate": "03/17/2023 07:06:57", "content": "Hello everyone,
\n Happy to be here with you, I had an issue to install and use a library in the competition .
\nThe library is nosiereduce, so the library is not present by default I call :
!pip install noisereduce\n\n noisereduce nr\nI precise here that I enabled the internet in the notebook, and after the installation I comment the
\n\"!pip install noisereduce\"
\nand I disabled the internet.
\nthis method doesn't work, and rise an error when I submit.
\nModuleNotFoundError: No module named 'noisereduce'
\nso, are we supposed to use only library installed by default ?
\nor there is a method to install new one ?
And thanks for your help
", "rawMarkdown": "Hello everyone,\n Happy to be here with you, I had an issue to install and use a library in the competition .\nThe library is **nosiereduce**, so the library is not present by default I call :\n```python\n!pip install noisereduce\n# and then\nimport noisereduce as nr\n\n```\nI precise here that I enabled the internet in the notebook, and after the installation I comment the \n`\"!pip install noisereduce\"`\nand I disabled the internet.\nthis method doesn't work, and rise an error when I submit.\n**ModuleNotFoundError: No module named 'noisereduce'**\nso, are we supposed to use only library installed by default ?\nor there is a method to install new one ? \n\nAnd thanks for your help", "votes": null }, { "id": "2193833", "postDate": "03/23/2023 14:34:37", "content": "Hi Aymen,
\nHave you found a solution to this problem? I am new here too and I wondered about this. I searched the discussions and found this post that describes a possible solution:
\nhttps://www.kaggle.com/c/severstal-steel-defect-detection/discussion/109679
\nMaybe that will do the trick?
", "rawMarkdown": "Hi Aymen,\n\nHave you found a solution to this problem? I am new here too and I wondered about this. I searched the discussions and found this post that describes a possible solution:\n\nhttps://www.kaggle.com/c/severstal-steel-defect-detection/discussion/109679\n\nMaybe that will do the trick?", "votes": null }, { "id": "2193835", "postDate": "03/23/2023 14:38:06", "content": "Here is the thread that I found first, that linked to the that one:
\nhttps://www.kaggle.com/discussions/product-feedback/93318
", "rawMarkdown": "Here is the thread that I found first, that linked to the that one:\n\nhttps://www.kaggle.com/discussions/product-feedback/93318", "votes": null }, { "id": "2194799", "postDate": "03/24/2023 06:52:42", "content": "Thank you so much for your help 🙏, I will check it out
", "rawMarkdown": "Thank you so much for your help 🙏, I will check it out", "votes": null } ], "comments": [ { "id": 2174124, "author_name": "shaghayeghreza", "author_url": "", "post_date": "03/08/2023 21:20:30", "content": "Hi. I am new to Kaggle. I can see that the competition has a code tab where people are uploading their codes. So, how it works? Why they are sharing their codes before the competition ends?
", "votes": null, "replies": [ { "id": 2181421, "author_name": "aymentabib", "author_url": "", "post_date": "03/14/2023 14:10:18", "content": "Hey Reza,
\nI'm new also in kaggle, and I find that practice is good to share knowledge between us.
\nanother point : if you read how kaggle handle ranking, you can understand also that is not about winning the first place but we can earn medals. and then you can not only earn medals in the competition but also medals related to your notebook and your discussions with other members. and if I'm not wrong you can share a version and keep working and optimizing your work in another version without sharing it.
Thanks for your information
", "votes": null, "replies": [] } ] } ] }, { "id": 2178047, "author_name": "bhavarththakur", "author_url": "", "post_date": "03/12/2023 03:41:52", "content": "👍👍👍👍👍
", "votes": null, "replies": [] }, { "id": 2185582, "author_name": "aymentabib", "author_url": "", "post_date": "03/17/2023 07:06:57", "content": "Hello everyone,
\n Happy to be here with you, I had an issue to install and use a library in the competition .
\nThe library is nosiereduce, so the library is not present by default I call :
!pip install noisereduce\n\n noisereduce nr\nI precise here that I enabled the internet in the notebook, and after the installation I comment the
\n\"!pip install noisereduce\"
\nand I disabled the internet.
\nthis method doesn't work, and rise an error when I submit.
\nModuleNotFoundError: No module named 'noisereduce'
\nso, are we supposed to use only library installed by default ?
\nor there is a method to install new one ?
And thanks for your help
", "votes": null, "replies": [ { "id": 2193833, "author_name": "vexatious", "author_url": "", "post_date": "03/23/2023 14:34:37", "content": "Hi Aymen,
\nHave you found a solution to this problem? I am new here too and I wondered about this. I searched the discussions and found this post that describes a possible solution:
\nhttps://www.kaggle.com/c/severstal-steel-defect-detection/discussion/109679
\nMaybe that will do the trick?
", "votes": null, "replies": [ { "id": 2193835, "author_name": "vexatious", "author_url": "", "post_date": "03/23/2023 14:38:06", "content": "Here is the thread that I found first, that linked to the that one:
\nhttps://www.kaggle.com/discussions/product-feedback/93318
", "votes": null, "replies": [] }, { "id": 2194799, "author_name": "aymentabib", "author_url": "", "post_date": "03/24/2023 06:52:42", "content": "Thank you so much for your help 🙏, I will check it out
", "votes": null, "replies": [] } ] } ] } ], "raw_markdown_by_id": { "2172700": "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!", "2174124": "Hi. I am new to Kaggle. I can see that the competition has a code tab where people are uploading their codes. So, how it works? Why they are sharing their codes before the competition ends?", "2178047": "👍👍👍👍👍", "2181421": "Hey Reza, \nI'm new also in kaggle, and I find that practice is good to share knowledge between us.\nanother point : if you read how kaggle handle ranking, you can understand also that is not about winning the first place but we can earn medals. and then you can not only earn medals in the competition but also medals related to your notebook and your discussions with other members. and if I'm not wrong you can share a version and keep working and optimizing your work in another version without sharing it.", "2183243": "Thanks for your information", "2185582": "Hello everyone,\n Happy to be here with you, I had an issue to install and use a library in the competition .\nThe library is **nosiereduce**, so the library is not present by default I call :\n```python\n!pip install noisereduce\n# and then\nimport noisereduce as nr\n\n```\nI precise here that I enabled the internet in the notebook, and after the installation I comment the \n`\"!pip install noisereduce\"`\nand I disabled the internet.\nthis method doesn't work, and rise an error when I submit.\n**ModuleNotFoundError: No module named 'noisereduce'**\nso, are we supposed to use only library installed by default ?\nor there is a method to install new one ? \n\nAnd thanks for your help", "2193833": "Hi Aymen,\n\nHave you found a solution to this problem? I am new here too and I wondered about this. I searched the discussions and found this post that describes a possible solution:\n\nhttps://www.kaggle.com/c/severstal-steel-defect-detection/discussion/109679\n\nMaybe that will do the trick?", "2193835": "Here is the thread that I found first, that linked to the that one:\n\nhttps://www.kaggle.com/discussions/product-feedback/93318", "2194799": "Thank you so much for your help 🙏, I will check it out" }, "source": "meta" }