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 to learn a bit more about site etiquette, Kaggle lingo, and how to enter a competition using Kaggle Notebooks.
\nReady to dive into this competition? Review the Overview Description and start to work with the Data!
\nAnd don't forget to check out the Getting Started resources for this competition. It provides some excellent starter material for working with the unique dataset!
\n\n", "messages": [ { "id": 1344196, "postDate": "2021-06-10T17:22:19.550Z", "content": "Remember: 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.
\n
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 to learn a bit more about site etiquette, Kaggle lingo, and how to enter a competition using Kaggle Notebooks.
\nReady to dive into this competition? Review the Overview Description and start to work with the Data!
\nAnd don't forget to check out the Getting Started resources for this competition. It provides some excellent starter material for working with the unique dataset!
\n\n", "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 to learn a bit more about [site etiquette](https://www.youtube.com/watch?v=aIus8si_Et0), [Kaggle lingo](https://www.youtube.com/watch?v=sEJHyuWKd-s), and [how to enter a competition using Kaggle Notebooks](https://www.youtube.com/watch?&v=GJBOMWpLpTQ).\n\nReady to dive into this competition? Review the [Overview Description](https://www.kaggle.com/c/mlb-player-digital-engagement-forecasting/overview) and start to work with the [Data](https://www.kaggle.com/c/mlb-player-digital-engagement-forecasting/data)!\n\nAnd don't forget to check out the [Getting Started](https://www.kaggle.com/c/mlb-player-digital-engagement-forecasting/overview/getting-started) resources for this competition. It provides some excellent starter material for working with the unique dataset!\n\n> **Remember**: 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).", "votes": 27 }, { "id": 1354887, "postDate": "2021-06-18T01:04:06.720Z", "content": "Remember: 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.
\n
This is my first kaggle competition and I have some questions about how the evaluation is made. When I call the mlb function to create the submission file, what exactly is the code reading as test data when I'm not running my code with the commit button?. And also, is creating a kaggle notebook and commiting the only way of submitting a prediction?
", "rawMarkdown": "This is my first kaggle competition and I have some questions about how the evaluation is made. When I call the mlb function to create the submission file, what exactly is the code reading as test data when I'm not running my code with the commit button?. And also, is creating a kaggle notebook and commiting the only way of submitting a prediction?\n\n" }, { "id": 1349693, "postDate": "2021-06-15T03:05:10.920Z", "content": "Thank you for providing a bit of summary for beginners and links. Much appreciated.
", "rawMarkdown": "Thank you for providing a bit of summary for beginners and links. Much appreciated." }, { "id": 1345114, "postDate": "2021-06-11T10:21:37.860Z", "content": "thank you but i have a question after ML what should i study?
", "rawMarkdown": "thank you but i have a question after ML what should i study?", "replies": [ { "id": 1355903, "postDate": "2021-06-18T15:56:27.703Z", "content": "Hi Nima! It depends on what your aim is. You could plan a career in data science. Check this video 👉 Why data science - top 3 reasons
", "rawMarkdown": "Hi Nima! It depends on what your aim is. You could plan a career in data science. Check this video 👉 [Why data science - top 3 reasons](https://youtu.be/GmNUXDeSqAg)" } ] }, { "id": 1351629, "postDate": "2021-06-16T13:28:54.423Z", "rawMarkdown": "", "isDeleted": true }, { "id": 1400627, "postDate": "2021-07-26T12:51:21.443Z", "content": "Thank you for this information.
", "rawMarkdown": "Thank you for this information." }, { "id": 1398336, "postDate": "2021-07-24T04:29:45.943Z", "content": "thanks for information
", "rawMarkdown": "thanks for information" }, { "id": 1355265, "postDate": "2021-06-18T07:41:22.763Z", "content": "Thank you!
", "rawMarkdown": "Thank you!" }, { "id": 1349322, "postDate": "2021-06-14T17:05:34.933Z", "content": "Thank you!
", "rawMarkdown": "Thank you!" } ], "comments": [ { "id": 1354887, "author_name": "HeyHey", "author_url": "", "post_date": "2021-06-18T01:04:06.720000", "content": "This is my first kaggle competition and I have some questions about how the evaluation is made. When I call the mlb function to create the submission file, what exactly is the code reading as test data when I'm not running my code with the commit button?. And also, is creating a kaggle notebook and commiting the only way of submitting a prediction?
", "votes": 0, "replies": [] }, { "id": 1349693, "author_name": "Hoosier Lake", "author_url": "", "post_date": "2021-06-15T03:05:10.920000", "content": "Thank you for providing a bit of summary for beginners and links. Much appreciated.
", "votes": 0, "replies": [] }, { "id": 1345114, "author_name": "nima jehan", "author_url": "", "post_date": "2021-06-11T10:21:37.860000", "content": "thank you but i have a question after ML what should i study?
", "votes": 0, "replies": [ { "id": 1355903, "author_name": "Chandrama Naha", "author_url": "", "post_date": "2021-06-18T15:56:27.703000", "content": "Hi Nima! It depends on what your aim is. You could plan a career in data science. Check this video 👉 Why data science - top 3 reasons
", "votes": 0, "replies": [] } ] }, { "id": 1351629, "author_name": "", "author_url": "", "post_date": "2021-06-16T13:28:54.423000", "content": "", "votes": 0, "replies": [] }, { "id": 1400627, "author_name": "starfishkenny", "author_url": "", "post_date": "2021-07-26T12:51:21.443000", "content": "Thank you for this information.
", "votes": 0, "replies": [] }, { "id": 1398336, "author_name": "Eko Yudhi Prastowo", "author_url": "", "post_date": "2021-07-24T04:29:45.943000", "content": "thanks for information
", "votes": 0, "replies": [] }, { "id": 1355265, "author_name": "lk137095576", "author_url": "", "post_date": "2021-06-18T07:41:22.763000", "content": "Thank you!
", "votes": 0, "replies": [] }, { "id": 1349322, "author_name": "Hugo Jiménez Muñoz", "author_url": "", "post_date": "2021-06-14T17:05:34.933000", "content": "Thank you!
", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1344196": "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 to learn a bit more about [site etiquette](https://www.youtube.com/watch?v=aIus8si_Et0), [Kaggle lingo](https://www.youtube.com/watch?v=sEJHyuWKd-s), and [how to enter a competition using Kaggle Notebooks](https://www.youtube.com/watch?&v=GJBOMWpLpTQ).\n\nReady to dive into this competition? Review the [Overview Description](https://www.kaggle.com/c/mlb-player-digital-engagement-forecasting/overview) and start to work with the [Data](https://www.kaggle.com/c/mlb-player-digital-engagement-forecasting/data)!\n\nAnd don't forget to check out the [Getting Started](https://www.kaggle.com/c/mlb-player-digital-engagement-forecasting/overview/getting-started) resources for this competition. It provides some excellent starter material for working with the unique dataset!\n\n> **Remember**: 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).", "1354887": "This is my first kaggle competition and I have some questions about how the evaluation is made. When I call the mlb function to create the submission file, what exactly is the code reading as test data when I'm not running my code with the commit button?. And also, is creating a kaggle notebook and commiting the only way of submitting a prediction?\n\n", "1349693": "Thank you for providing a bit of summary for beginners and links. Much appreciated.", "1345114": "thank you but i have a question after ML what should i study?", "1351629": "", "1400627": "Thank you for this information.", "1398336": "thanks for information", "1355265": "Thank you!", "1349322": "Thank you!" } }