A million thanks to @jessililee for uploading the @nook_plaza #AnimalCrossingNewHorizons dataset to Kaggle! You can check it out and create your own analyses here: https://t.co/qzEiQBsiCt pic.twitter.com/1dzAUqmDUc
— Kaggle (@kaggle) May 26, 2020
A million thanks to @jessililee for uploading the @nook_plaza #AnimalCrossingNewHorizons dataset to Kaggle! You can check it out and create your own analyses here: https://t.co/qzEiQBsiCt pic.twitter.com/1dzAUqmDUc
— Kaggle (@kaggle) May 26, 2020
A new dataset and challenge: detecting hateful memes. https://t.co/JbXnx604tX
— Yann LeCun (@ylecun) May 12, 2020
Just launched: Global Wheat Detection!
— Kaggle (@kaggle) May 5, 2020
Think you can identify wheat heads using image analysis? Get started today and you might take home part of a $15,000 prize pool: https://t.co/H3edcv77wr pic.twitter.com/7ZpFci0qRA
"This paper introduces a new task of politeness transfer which involves converting non-polite sentences to polite sentences while preserving the meaning.
— 👩💻 DynamicWebPaige @ 127.0.0.1 🏠 (@DynamicWebPaige) May 1, 2020
We also provide a dataset of 1.39M+ instances automatically labeled for politeness."https://t.co/sKXGOId2mu#KindTwitter❤️ pic.twitter.com/y1XA9NylP6
This is interesting data from New York City, which has been i) tracking probable in addition to confirmed deaths and ii) tracking deaths on the date they think the death actually occurred, not when it shows up in their records. https://t.co/O1f8OmAlrI
— Nate Silver (@NateSilver538) April 27, 2020
I’ve always wanted to learn Yoga…
— Denny Britz (@dennybritz) April 23, 2020
Now there’s a dataset. Yoga-82: A New Dataset for Fine-grained Classification of Human Poses: https://t.co/Qt9DjXrxUX pic.twitter.com/HMpYVLyCei
Discovered this dataset today, which seems like an amazing test case for CSV readers' ability to handle Unicode: https://t.co/7LGoM9ViAx
— John Myles White (@johnmyleswhite) April 17, 2020
For those of you interested in exploring potential relationships between weather and #COVID19, Kaggler Davide Bonin has joined the Johns Hopkins dataset with NOAA's GSOD dataset: https://t.co/xggTjyVcyU pic.twitter.com/kRB8MdZLBn
— Kaggle (@kaggle) April 14, 2020
I'm excited to announce XTREME, a new benchmark that covers 9 tasks and 40 typologically diverse languages.
— Sebastian Ruder (@seb_ruder) April 13, 2020
Paper: https://t.co/ZjBIYK6QcX
Blog post: https://t.co/L0SiDRRHMX
Code: https://t.co/QEmw5ZGHoN pic.twitter.com/YVo0T9gT63
Announcing XTREME, a new #NaturalLanguageProcessing benchmark for cross-lingual generalization, which covers 40 typologically diverse languages using nine tasks that collectively require reasoning about different levels of syntax or semantics. Learn more ↓https://t.co/F7pgTQdbuo
— Google AI (@GoogleAI) April 13, 2020
The frequency of random seeds between 0 and 1000 on github (data from https://t.co/xwutMzNI2N) pic.twitter.com/Zmp7mwMWil
— Jake VanderPlas (@jakevdp) April 8, 2020
Change in people visiting retail and recreation locations:
— Anthony Goldbloom (@antgoldbloom) April 6, 2020
Italy: -94%
Spain: -94%
New Zealand: 91%
UK: -85%
India: -77%
Brazil: -71%
Israel: -67%
US: -47%
Australia: -45%
Japan: -26%
Sweden: -24%
South Korea: -19%
Taiwan: -9%https://t.co/YpAfQ4OlfZ