Dear friends,

Welcome to the latest edition of the Sunday Briefing.

This week we're fresh off yesterdays Meetup Event on Time Series modeling. You can checkout Reshama Shaikh's blog post for some photos. Thank you again to all of you who spent your Saturday with us. You helped make it a great success. 

On a less positive note, there's also some bad news on the Data For Science front. Due to CoVID-19 concerns, O'Reilly has decided to cancel this years edition of the Strata and AI conference in San Jose and with it our scheduled 2-day training on Time series. We apologize to those of you who were looking forward to it. We're planning hold it instead in the NYC edition of Strata/AI in September and we'll keep you posted. Hopefully you'll be able to make it then. 

This week we take advantage of the fact that CoVID19 and epidemic modeling are in the news to highlight some of the applications of Data Science and Machine Learning to the epidemiological and infectious diseases domains. Deep Mind just published their approach for Computational predictions of protein structures associated with COVID-19 and the New York times has a nice article on how to use the interest generated by the news cycle to Teach About Data and Statistics and a recent pre-preprint on how to use Bayesian approaches for early outbreak detection. We round up the week with a survey paper on Time Series Data Augmentation and an investigation on the connections between Transformers and Graph Neural Networks

Finally, in our video of the week, Kirstie Whitaker presents a how to guide for reproducible research at last years PyData London.

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Semper discentes,

The D4S team