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Zindi Crowdsources COVID19 solutions through virtual hackathons
African data science competition platform Zindi has released the first of its machine learning solutions to help fight the COVID-19 pandemic. The solution, a model that can predict air pollution levels using satellite data, comes from Zindi’s virtual hackathon series #ZindiWeekendz.
SPONSORED BY Microsoft, #ZindiWeekendz is a series of virtual hackathons running every weekend throughout the months of April and May, specifically focused on the health, social, and economic impacts of COVID-19. All solutions will be shared on GitHub and are freely available for government, academic and private sector actors to use in their battle against COVID-19.
During #ZindiWeekendz, data scientists build practical solutions to some of the public health and economic challenges Africa and the world face as a result of the COVID-19 crisis.
Since the beginning of April, Zindi has hosted challenges to map the households in South Africa most vulnerable to COVID-19, to predict air quality from satellite imagery, and to build a model that can identify whether a person in an image is wearing a face mask. Every solution that comes out of these challenges is freely available for anyone wanting to put them to use, and Zindi will also be making its own efforts to get these models used by various organisations.
Future #ZindiWeekendz challenges will continue to explore ways that data science, machine learning, and artificial intelligence can improve social, economic, and health outcomes of COVID-19. Zindi will continue to work with governments, companies, and non-profit organisations to make sure these solutions end up in the hands of those who need them most.
If you’re interested in helping Zindi make a difference, you can join the next #ZindiWeekendz hackathon or suggest a relevant data set. ai
