GLUE now has a human performance estimate for all nine tasks! Overall score 86.9. Thanks to @meloncholist. https://t.co/GNGW55uo5M
— Sam Bowman (@sleepinyourhat) February 3, 2019
GLUE now has a human performance estimate for all nine tasks! Overall score 86.9. Thanks to @meloncholist. https://t.co/GNGW55uo5M
— Sam Bowman (@sleepinyourhat) February 3, 2019
IBM releases ‘Diversity in Faces’, a dataset of over 1 million #annotations to help reduce facial recognition bias: https://t.co/PMAi8CGHoz#DataScience #MachineLearning #BigData #DeepLearning #AI #ComputerVision #AIethics pic.twitter.com/jyXgz5Kihh
— Kirk Borne (@KirkDBorne) January 30, 2019
Detecting street art in Instagram pictures: https://t.co/pIu9Ly9Jrj
— François Chollet (@fchollet) January 29, 2019
TFDV (https://t.co/Lv4n5Hnnfw) is a super handy tool to quickly analyze a new dataset, discover its schema automagically, detect outliers & train/test discrepancies, monitor that inputs remain consistent in production, and more.
— Aurélien Geron (@aureliengeron) January 25, 2019
Try it out using Colab: https://t.co/OfigtqSFOe
natural-questions - https://t.co/TZKJ8QcPyE
— Python Trending (@pythontrending) January 24, 2019
Natural Questions: A new QA dataset consisting of 300,000+ naturally occurring questions (posed to Google search) with human provided long & short answers based on Wikipedia. Looks like an exciting new benchmark!
— Sebastian Ruder (@seb_ruder) January 24, 2019
Paper: https://t.co/JzRg3E8VQg
Competition: https://t.co/avU2M0Wa9U pic.twitter.com/DIsl11cvX0
I believe this new dataset that we just released is going to be a pretty challenging and interesting one for NLP and question answering research.
— Jeff Dean (@JeffDean) January 23, 2019
"where is blood pumped after it leaves the right ventricle?"
"who did hawaii belong to before 1959 purchase?" https://t.co/uREZAyKd4H
Announcing CheXpert! Large dataset of chest X-rays co-released with MIT's MIMIC-CXR dataset. Join our competition to test your chest X-ray interpretation model: https://t.co/ldWBwjoZKn@jeremy_irvin16 @pranavrajpurkar @mlko53 @curtlanglotz @mattlungrenMD @Stanford #AAAI19
— Andrew Ng (@AndrewYNg) January 23, 2019
Film genre popularity, 1910-2018. #movies #datavizhttps://t.co/WZGHOQGgw9 pic.twitter.com/FLsmdIbcM1
— Randy Olson (@randal_olson) January 15, 2019
Can you predict when an earthquake will hit? Get shakin' on our latest competition, hosted by @LosAlamosNatLab. There's $50k in prizes and potentially lifesaving research on the line. Get started: https://t.co/DbbVLAwOaQ pic.twitter.com/IlrgC3UVIh
— Kaggle (@kaggle) January 11, 2019
We put together a new data set on Cabinet turnover! https://t.co/gRxKPJLlXi pic.twitter.com/z26tCDF1Yb
— Micah Cohen (@micahcohen) January 8, 2019
Kuzushiji-MNIST/49/Kanji released officially on @Kaggle @KaggleDatasets! 🎉
— Mikel Bober-Irizar (@mikb0b) January 6, 2019
Check it out: https://t.co/Z74yRlis0S ✨✨
Starter kernel by @A_K_Nain: https://t.co/PIAP7Ycq9Q pic.twitter.com/Hf1pI5oaAj