Difference between revisions of "COVID-19"
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* [[Kaggle]] | * [[Kaggle]] | ||
| + | * [[Kaggle Competitions]] | ||
** [http://www.kaggle.com/competitions Competitions | Kaggle] | ** [http://www.kaggle.com/competitions Competitions | Kaggle] | ||
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| + | The primary goal of Kaggle’s COVID-19 effort is to find factors that impact the transmission of COVID-19 (particularly those that map to the NASEM/WHO open scientific questions). You've already shown great results in producing meaningful insights to help address the pandemic! | ||
| + | * [http://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge COVID-19 Open Research Dataset Challenge (CORD-19)] in response to the COVID-19 pandemic | ||
| − | + | * [http://www.kaggle.com/c/covid19-global-forecasting-week-2?utm_medium=email&utm_source=intercom&utm_campaign=covid19-forecastinwk2-email COVID-19 Global Forecasting Challenge: week 2 of Kaggle's COVID19 forecasting series]: The primary goal is not only to forecast accurately, but to find factors that impact transmission rate of COVID-19. You are encouraged to pull in, curate, and share data sources that might be helpful. If you find variables that look like they impact the transmission rate, please share your findings in a notebook. | |
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| + | * COVID-19 Dataset Challenge: Kagglers will need to find, curate, share -- and join -- useful public datasets. You can review the relevant threads for sharing datasets and discussing dataset ideas to get an idea of the types of things that Kagglers find most useful. For this challenge we are only considering public datasets on Kaggle. | ||
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Acknowledgments | Acknowledgments | ||
John Hopkins University CSSE for making the data available to the public and the White House OSTP for pulling together the key open questions. | John Hopkins University CSSE for making the data available to the public and the White House OSTP for pulling together the key open questions. | ||
Revision as of 09:03, 28 March 2020
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The primary goal of Kaggle’s COVID-19 effort is to find factors that impact the transmission of COVID-19 (particularly those that map to the NASEM/WHO open scientific questions). You've already shown great results in producing meaningful insights to help address the pandemic!
- COVID-19 Open Research Dataset Challenge (CORD-19) in response to the COVID-19 pandemic
- COVID-19 Global Forecasting Challenge: week 2 of Kaggle's COVID19 forecasting series: The primary goal is not only to forecast accurately, but to find factors that impact transmission rate of COVID-19. You are encouraged to pull in, curate, and share data sources that might be helpful. If you find variables that look like they impact the transmission rate, please share your findings in a notebook.
- COVID-19 Dataset Challenge: Kagglers will need to find, curate, share -- and join -- useful public datasets. You can review the relevant threads for sharing datasets and discussing dataset ideas to get an idea of the types of things that Kagglers find most useful. For this challenge we are only considering public datasets on Kaggle.
Acknowledgments
John Hopkins University CSSE for making the data available to the public and the White House OSTP for pulling together the key open questions.
Next important deadlines
Forecasting: April 1, 2020 Entry deadline
Datasets: April 3, 2020 Entry deadline
Get started now
COVID-19 Global Forecasting Challenge (Week 2)
COVID-19 Dataset Challenge
Thanks for continuing to do what you can to help advance our global understanding of COVID-19,
Kaggle Team
