\n
![\"drawing\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F19099%2Fad8714e9a1d2b468697d1052dbd7fda8%2F2023-10-29%20%2015.46.35.png?generation=1698583615741236&alt=media\")
Hi fellow Kagglers,
\nI have created the dataset and the example kernel to make some analytics on the kernels, which were created for this competition.
\nIn the kernel you can see several interesting points like:
\nTo make it more interesting to check here are some results.
\nHere we can congrats @carlmcbrideellis for the 1st place with the amazing 4 gold and 1 silver medals, @werus23 for the 2nd place with 3 gold medals and @renatoreggiani for the 3rd place with 1 gold, 3 silver and 2 bronze medals:
\n
The full kernels graph for this competition looks like (you can see it in bigger size if you click on it in kernel with the right mouse button and open it in another tab):
\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F19099%2F13a73a92b72532cebc6d014212b9b42e%2FChild_sleep_states.png?generation=1698583844955546&alt=media\")
The most interesting part here with 7 levels is:
\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F19099%2Fea2607039715c1921bf573388a92d7a0%2F2023-10-29%20%2015.34.38.png?generation=1698583866996965&alt=media\")
I have used the kernel IDs in the graph to make it more readable so to find your kernel ID you can check it in the dataset by your name or kernel title.
\nIf we use this graph and calculate the cumulative number of upvotes using the forks, we can receive the table like:
\n![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-forum-message-attachments/o/inbox%2F19099%2Fed886f3f2d35e051fd011d486fc64e10%2F2023-10-29%20%2015.41.11.png?generation=1698583959876862&alt=media\")
The current top-3 by cumulative votes is:
\nLooking forward for your comments, suggestions and insights!
\nAlex
", "messages": [ { "id": 2503788, "postDate": "2023-10-29T12:58:47.707Z", "content": "Hi fellow Kagglers,
\nI have created the dataset and the example kernel to make some analytics on the kernels, which were created for this competition.
\nIn the kernel you can see several interesting points like:
\nTo make it more interesting to check here are some results.
\nHere we can congrats @carlmcbrideellis for the 1st place with the amazing 4 gold and 1 silver medals, @werus23 for the 2nd place with 3 gold medals and @renatoreggiani for the 3rd place with 1 gold, 3 silver and 2 bronze medals:
\n
The full kernels graph for this competition looks like (you can see it in bigger size if you click on it in kernel with the right mouse button and open it in another tab):
\n
The most interesting part here with 7 levels is:
\n
I have used the kernel IDs in the graph to make it more readable so to find your kernel ID you can check it in the dataset by your name or kernel title.
\nIf we use this graph and calculate the cumulative number of upvotes using the forks, we can receive the table like:
\n
The current top-3 by cumulative votes is:
\nLooking forward for your comments, suggestions and insights!
\nAlex
", "rawMarkdown": "Hi fellow Kagglers,\n\nI have created [the dataset](https://www.kaggle.com/datasets/alexryzhkov/cm-institute-detect-sleep-states-kernel-stats/) and [the example kernel](https://www.kaggle.com/code/alexryzhkov/get-kernels-stats-cm-institute-sleep-states) to make some analytics on the kernels, which were created for this competition.\n\nIn the kernel you can see several interesting points like:\n- Top-20 kernel creators\n- Performance Tiers of kernel creators\n- Kernels medals stats\n- Medals for kernels creators (top-20)\n- Kernels languages\n- How many kernels are the forks?\n- How many lines are changed in forks?\n- Does the kernel use GPU or not?\n- Upvotes vs views and Upvotes vs NumberOfComments\n- Most commented kernels\n- **Kernel forks graph** and tops on it\n\nTo make it more interesting to check here are some results.\n\n### Medals for kernels\n\nHere we can congrats @carlmcbrideellis for the 1st place with the amazing 4 gold and 1 silver medals, @werus23 for the 2nd place with 3 gold medals and @renatoreggiani for the 3rd place with 1 gold, 3 silver and 2 bronze medals:\n\n\n### Forks graph\n\nThe full kernels graph for this competition looks like (you can see it in bigger size if you click on it in kernel with the right mouse button and open it in another tab):\n\n\n\nThe most interesting part here with **7 levels** is:\n\n\n\nI have used the kernel IDs in the graph to make it more readable so to find your kernel ID you can check it in the dataset by your name or kernel title.\n\nIf we use this graph and calculate the cumulative number of upvotes using the forks, we can receive the table like:\n\n\n\nThe current top-3 by cumulative votes is:\n- [Zzzs: Random Forest model starter](https://www.kaggle.com/code/carlmcbrideellis/zzzs-random-forest-model-starter) from @carlmcbrideellis with 423 votes\n- [Feature Engineering and Random Forest Prediction](https://www.kaggle.com/code/lccburk/feature-engineering-and-random-forest-prediction) from @lccburk with 225 votes\n- [XGBOOST STARTER NOTEBOOK](https://www.kaggle.com/code/shivamsingh17072001/xgboost-starter-notebook) from @shivamsingh17072001 with 211 votes\n\nLooking forward for your comments, suggestions and insights!\n\nAlex ",
"votes": 21
}
],
"comments": [],
"raw_markdown_by_id": {
"2503788": "Hi fellow Kagglers,\n\nI have created [the dataset](https://www.kaggle.com/datasets/alexryzhkov/cm-institute-detect-sleep-states-kernel-stats/) and [the example kernel](https://www.kaggle.com/code/alexryzhkov/get-kernels-stats-cm-institute-sleep-states) to make some analytics on the kernels, which were created for this competition.\n\nIn the kernel you can see several interesting points like:\n- Top-20 kernel creators\n- Performance Tiers of kernel creators\n- Kernels medals stats\n- Medals for kernels creators (top-20)\n- Kernels languages\n- How many kernels are the forks?\n- How many lines are changed in forks?\n- Does the kernel use GPU or not?\n- Upvotes vs views and Upvotes vs NumberOfComments\n- Most commented kernels\n- **Kernel forks graph** and tops on it\n\nTo make it more interesting to check here are some results.\n\n### Medals for kernels\n\nHere we can congrats @carlmcbrideellis for the 1st place with the amazing 4 gold and 1 silver medals, @werus23 for the 2nd place with 3 gold medals and @renatoreggiani for the 3rd place with 1 gold, 3 silver and 2 bronze medals:\n\n\n### Forks graph\n\nThe full kernels graph for this competition looks like (you can see it in bigger size if you click on it in kernel with the right mouse button and open it in another tab):\n\n\n\nThe most interesting part here with **7 levels** is:\n\n\n\nI have used the kernel IDs in the graph to make it more readable so to find your kernel ID you can check it in the dataset by your name or kernel title.\n\nIf we use this graph and calculate the cumulative number of upvotes using the forks, we can receive the table like:\n\n\n\nThe current top-3 by cumulative votes is:\n- [Zzzs: Random Forest model starter](https://www.kaggle.com/code/carlmcbrideellis/zzzs-random-forest-model-starter) from @carlmcbrideellis with 423 votes\n- [Feature Engineering and Random Forest Prediction](https://www.kaggle.com/code/lccburk/feature-engineering-and-random-forest-prediction) from @lccburk with 225 votes\n- [XGBOOST STARTER NOTEBOOK](https://www.kaggle.com/code/shivamsingh17072001/xgboost-starter-notebook) from @shivamsingh17072001 with 211 votes\n\nLooking forward for your comments, suggestions and insights!\n\nAlex "
}
}