Hi Kagglers,
\nWe’re happy to announce the conclusion of the Google - Fast or Slow? Predict AI Model Runtime competition. Thank you everyone for your participation!
\nThis competition ended with 5232 registrations and 792 participants on 616 teams. We had 10507 submissions from 66 countries. For 153 users (including 47 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!
\nThe top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.
\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.
\nWe highly encourage you to post a solution write-up about your approach and solution in the forums. We’re awarding swag to the 50 teams with the most upvotes on their solution write-ups two weeks after the competition’s final submission deadline.
\nTo be eligible, the solution write-ups must be linked as an official writeup (see instructions) and the write-up should meet the criteria outlined in our new quality rubric. We’re using upvotes as a measure of quality and helpfulness, please be sure you keep this in mind when upvoting others' work. Evidence of upvote gaming will result in disqualification and/or account banning. Details can be found here.
\nThanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!
\nHappy Modeling!
\nKaggle Team
Hi Kagglers,
\nWe’re happy to announce the conclusion of the Google - Fast or Slow? Predict AI Model Runtime competition. Thank you everyone for your participation!
\nThis competition ended with 5232 registrations and 792 participants on 616 teams. We had 10507 submissions from 66 countries. For 153 users (including 47 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking!
\nThe top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.
\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact compliance. Please fill in all the fields honestly.
\nWe highly encourage you to post a solution write-up about your approach and solution in the forums. We’re awarding swag to the 50 teams with the most upvotes on their solution write-ups two weeks after the competition’s final submission deadline.
\nTo be eligible, the solution write-ups must be linked as an official writeup (see instructions) and the write-up should meet the criteria outlined in our new quality rubric. We’re using upvotes as a measure of quality and helpfulness, please be sure you keep this in mind when upvoting others' work. Evidence of upvote gaming will result in disqualification and/or account banning. Details can be found here.
\nThanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!
\nHappy Modeling!
\nKaggle Team
Congratulation to all the winners and thank you so much for participating in this competition. This is my first time running a Kaggle competition, and I had no idea how it would turn out. I was especially nervous how much interest we would get since the topic is in a very specific domain. I was afraid that the compiler part might scare many people away! However, it turned out to be a very rewarding experience despite a few hic-ups (data corruption and partial test data leakage). I especially love how people shared their knowledge throughout the competition. I'm slowing going through the solutions but already learned many new tricks!
", "rawMarkdown": "Congratulation to all the winners and thank you so much for participating in this competition. This is my first time running a Kaggle competition, and I had no idea how it would turn out. I was especially nervous how much interest we would get since the topic is in a very specific domain. I was afraid that the compiler part might scare many people away! However, it turned out to be a very rewarding experience despite a few hic-ups (data corruption and partial test data leakage). I especially love how people shared their knowledge throughout the competition. I'm slowing going through the solutions but already learned many new tricks!", "votes": null }, { "id": "2534572", "postDate": "11/22/2023 18:25:48", "content": "Thank you @mangpophothilimthana (and other hosts) for your dedication to run this competition. The problem by itself is really interesting but, from the competitors' point of view, makes a lot of difference when the hosts are also engaged. You guys did an amazing job of helping us understand the data!
", "rawMarkdown": "Thank you @mangpophothilimthana (and other hosts) for your dedication to run this competition. The problem by itself is really interesting but, from the competitors' point of view, makes a lot of difference when the hosts are also engaged. You guys did an amazing job of helping us understand the data!", "votes": null } ], "comments": [ { "id": 2533435, "author_name": "mangpophothilimthana", "author_url": "", "post_date": "11/21/2023 23:34:20", "content": "Congratulation to all the winners and thank you so much for participating in this competition. This is my first time running a Kaggle competition, and I had no idea how it would turn out. I was especially nervous how much interest we would get since the topic is in a very specific domain. I was afraid that the compiler part might scare many people away! However, it turned out to be a very rewarding experience despite a few hic-ups (data corruption and partial test data leakage). I especially love how people shared their knowledge throughout the competition. I'm slowing going through the solutions but already learned many new tricks!
", "votes": null, "replies": [ { "id": 2534572, "author_name": "arc144", "author_url": "", "post_date": "11/22/2023 18:25:48", "content": "Thank you @mangpophothilimthana (and other hosts) for your dedication to run this competition. The problem by itself is really interesting but, from the competitors' point of view, makes a lot of difference when the hosts are also engaged. You guys did an amazing job of helping us understand the data!
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "2532258": "Hi Kagglers,\n\nWe’re happy to announce the conclusion of the Google - Fast or Slow? Predict AI Model Runtime competition. Thank you everyone for your participation!\n\nThis competition ended with 5232 registrations and 792 participants on 616 teams. We had 10507 submissions from 66 countries. For 153 users (including 47 in the top 100!), this was their first competition. Thank you all for your hard work in this competition and congratulations to our winners and to those who gained a new ranking! \n\nThe top potential winning teams will be contacted via email for the next steps. We look forward to learning more about their winning solutions.\n\nWe've cleaned the leaderboard and disqualified some teams that have violated the rules. If you think you were removed by mistake, or believe you have evidence that suggests another team cheated, please contact [compliance](https://www.kaggle.com/compliance). Please fill in all the fields honestly.\n\nWe highly encourage you to post a solution write-up about your approach and solution in the forums. We’re awarding swag to the 50 teams with the most upvotes on their solution write-ups two weeks after the competition’s final submission deadline.\n\nTo be eligible, the solution write-ups must be linked as an official writeup (see [instructions](https://www.kaggle.com/discussions/product-feedback/373153)) and the write-up should meet the criteria outlined in our [new quality rubric](https://www.kaggle.com/solution-write-up-documentation). We’re using upvotes as a measure of quality and helpfulness, please be sure you keep this in mind when upvoting others' work. Evidence of upvote gaming will result in disqualification and/or account banning. Details can be found [here](https://www.kaggle.com/discussions/general/427114).\n\nThanks for continuing to make Kaggle a great place to learn, practice, and test data science techniques!\n\nHappy Modeling!\nKaggle Team", "2533435": "Congratulation to all the winners and thank you so much for participating in this competition. This is my first time running a Kaggle competition, and I had no idea how it would turn out. I was especially nervous how much interest we would get since the topic is in a very specific domain. I was afraid that the compiler part might scare many people away! However, it turned out to be a very rewarding experience despite a few hic-ups (data corruption and partial test data leakage). I especially love how people shared their knowledge throughout the competition. I'm slowing going through the solutions but already learned many new tricks!", "2534572": "Thank you @mangpophothilimthana (and other hosts) for your dedication to run this competition. The problem by itself is really interesting but, from the competitors' point of view, makes a lot of difference when the hosts are also engaged. You guys did an amazing job of helping us understand the data!" }, "source": "meta" }