Our 5th annual Data Science Bowl competition is now live! ⁰Help educators around the globe better understand how kids learn. ⁰Read the details and get started today: https://t.co/oyhvnKJAnZ #DataSciBowl pic.twitter.com/WCIWzO5QPm
— Kaggle (@kaggle) October 24, 2019
Help the environment by predicting (and reducing) how much energy 💡 a building will consume and you could win part of a $25K prize pool. 🌇
— Kaggle (@kaggle) October 16, 2019
Learn more https://t.co/WzDKBLIGa5 #justlaunched #kagglecompetition pic.twitter.com/pE2Ey0HoFM
Both #rstats and #python used in the GitHub repo for this important analysis #ddj https://t.co/BkwMKebMcc https://t.co/GEzZ9fnWUX
— Sharon Machlis (@sharon000) October 13, 2019
We are releasing a new benchmark and data set to evaluate performance across various neural code search techniques to make it easier to evaluate a new model on a common set of questions. https://t.co/bpMtJcfY2c pic.twitter.com/rUYHx9awgf
— Facebook AI (@facebookai) October 3, 2019
📢 @GitHub is releasing a large dataset for natural language processing and machine learning. It's a large parallel corpus of code and natural language, with benchmarks on IR tasks. Leaderboard is hosted by @weights_biases: https://t.co/rSKbvkfX4S
— Hamel Husain (@HamelHusain) September 26, 2019
Our two-step, self-supervised approach to extractive question answering (QA) first trains a model to generate questions, then uses those questions to train a standard extractive QA model.https://t.co/FDSiMAyhuo pic.twitter.com/7JQStT0915
— Facebook AI (@facebookai) September 24, 2019
In collaboration with @Jigsaw and in partnership w/ the FaceForensics video benchmark team, we are excited to release a large dataset of visual deepfakes to directly support deepfake detection efforts. Learn more and find the data at https://t.co/0faXdciuxC pic.twitter.com/m8vM3GGbdY
— Google AI (@GoogleAI) September 24, 2019
Detecting deepfakes is one of the most important challenges ahead of us. Following our release of a synthetic audio dataset in Jan, we're releasing a large dataset of visual deepfakes to support researchers working on synthetic video detection #GoogleAIhttps://t.co/sDW7BP34qL
— Sundar Pichai (@sundarpichai) September 24, 2019
MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection
— hardmaru (@hardmaru) September 23, 2019
I’m sure this dataset can be used in ways outside of the original intended purpose...https://t.co/RqB8N6Yieo https://t.co/78QsVmIXGO
I believe this is the first time a dataset like this has been released - this is really exciting! https://t.co/l0H2mihMn3
— Jeremy Howard (@jeremyphoward) September 22, 2019
@RSNA Intracranial Hemorrhage Detection @kaggle competition starter pack using @fastdotai
— Radek Osmulski (@radekosmulski) September 20, 2019
✅github repository: https://t.co/BLlNEuKlmk
✅competition website: https://t.co/HcP3HTUPgD
✅approach overview: https://t.co/0aNSrxFyRn
✅@fastdotai forum post: https://t.co/6Cag5b5v1m pic.twitter.com/hFmE0mG1Q0
Help detect serious head injuries by participating in our latest competition, Intracranial Hemorrhage Detection by @RSNA | Read more and Join today! https://t.co/bQOu4ZYfK9 pic.twitter.com/vyl0Todx3M
— Kaggle (@kaggle) September 18, 2019
