![\"\"](\"https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F347463%2Fa830c7ea6b8f20dbd1e73e1dc893b339%2Fpku-autonomous-driving-shakeup.png?generation=1579707058680797&alt=media\")
Congrats to all winners - seeing write-ups so soon after the deadline is a sure sign of confidence in your performance! (Which would make an interesting contest in itself - wagering on who finishes where...)
\n\nJust testing out my old scatterplot code before the 2019 Data Science Bowl ends - here is a plot for Peking University/Baidu - Autonomous Driving :)
\n\nThe medal zones look very solid, most shake-up in the mid-field.
\n\n
The stats are:\n - shake-up = 0.05122\n - top 10% shake-up = 0.01003\n - gold shake-up = 0.00240
\n\nBiggest fall: 294 places (I won't point anyone out)
\n\nBest risers up the leaderboard were:
\n\nThere's a Notebook here here that generates plots for all competitions - so you can see how it compares to the growing collection :D
", "messages": [ { "id": "725905", "postDate": "01/22/2020 15:36:16", "content": "Congrats to all winners - seeing write-ups so soon after the deadline is a sure sign of confidence in your performance! (Which would make an interesting contest in itself - wagering on who finishes where...)
\n\nJust testing out my old scatterplot code before the 2019 Data Science Bowl ends - here is a plot for Peking University/Baidu - Autonomous Driving :)
\n\nThe medal zones look very solid, most shake-up in the mid-field.
\n\n
The stats are:\n - shake-up = 0.05122\n - top 10% shake-up = 0.01003\n - gold shake-up = 0.00240
\n\nBiggest fall: 294 places (I won't point anyone out)
\n\nBest risers up the leaderboard were:
\n\nThere's a Notebook here here that generates plots for all competitions - so you can see how it compares to the growing collection :D
", "rawMarkdown": "Congrats to all winners - seeing write-ups so soon after the deadline is a sure sign of confidence in your performance! (Which would make an interesting contest in itself - wagering on who finishes where...)\n\nJust testing out my old scatterplot code before the 2019 Data Science Bowl ends - here is a plot for Peking University/Baidu - Autonomous Driving :)\n\nThe medal zones look very solid, most shake-up in the mid-field.\n\n\n\n\nThe stats are:\n - shake-up = 0.05122\n - top 10% shake-up = 0.01003\n - gold shake-up = 0.00240\n\nBiggest fall: 294 places (I won't point anyone out)\n\nBest risers up the leaderboard were:\n\n - ***+204*** [447 → 243] *TKM* (@takumidejima )\n - ***+203*** [434 → 231] *Jing Wang* (@thefatcat )\n - ***+200*** [433 → 233] *AT081134* (@sabermywife )\n - ***+200*** [432 → 232] *Vitalii Mokin* (@vbmokin )\n - ***+197*** [435 → 238] *Greg Hamel* (@hamelg )\n - ***+196*** [452 → 256] *BaekJeongHun* (@ku21fan )\n - ***+196*** [406 → 210] *Rick* (@uestctubiao )\n - ***+196*** [421 → 225] *Xiangdi Liu* (@stannnn )\n - ***+194*** [431 → 237] *isolja* (@isolja )\n - ***+193*** [429 → 236] *Nikita Hismatov* (@nikitahismatov )\n\n\nThere's a [Notebook here][1] here that generates plots for **all** competitions - so you can see how it compares to the growing collection :D\n\n\n [1]: https://www.kaggle.com/jtrotman/meta-kaggle-scatter-plot-competition-shake-up", "votes": null }, { "id": "725990", "postDate": "01/22/2020 17:35:37", "content": "Great\nInformative Stats!! @jtrotman
", "rawMarkdown": "Great\nInformative Stats!! @jtrotman", "votes": null } ], "comments": [ { "id": 725990, "author_name": "veeralakrishna", "author_url": "", "post_date": "01/22/2020 17:35:37", "content": "Great\nInformative Stats!! @jtrotman
", "votes": null, "replies": [] } ], "raw_markdown_by_id": { "725905": "Congrats to all winners - seeing write-ups so soon after the deadline is a sure sign of confidence in your performance! (Which would make an interesting contest in itself - wagering on who finishes where...)\n\nJust testing out my old scatterplot code before the 2019 Data Science Bowl ends - here is a plot for Peking University/Baidu - Autonomous Driving :)\n\nThe medal zones look very solid, most shake-up in the mid-field.\n\n\n\n\nThe stats are:\n - shake-up = 0.05122\n - top 10% shake-up = 0.01003\n - gold shake-up = 0.00240\n\nBiggest fall: 294 places (I won't point anyone out)\n\nBest risers up the leaderboard were:\n\n - ***+204*** [447 → 243] *TKM* (@takumidejima )\n - ***+203*** [434 → 231] *Jing Wang* (@thefatcat )\n - ***+200*** [433 → 233] *AT081134* (@sabermywife )\n - ***+200*** [432 → 232] *Vitalii Mokin* (@vbmokin )\n - ***+197*** [435 → 238] *Greg Hamel* (@hamelg )\n - ***+196*** [452 → 256] *BaekJeongHun* (@ku21fan )\n - ***+196*** [406 → 210] *Rick* (@uestctubiao )\n - ***+196*** [421 → 225] *Xiangdi Liu* (@stannnn )\n - ***+194*** [431 → 237] *isolja* (@isolja )\n - ***+193*** [429 → 236] *Nikita Hismatov* (@nikitahismatov )\n\n\nThere's a [Notebook here][1] here that generates plots for **all** competitions - so you can see how it compares to the growing collection :D\n\n\n [1]: https://www.kaggle.com/jtrotman/meta-kaggle-scatter-plot-competition-shake-up", "725990": "Great\nInformative Stats!! @jtrotman" }, "source": "meta" }