Dear friends,

Welcome to the June 14 edition of the Sunday Briefing, where we continue our celebration of the 1 year anniversary of this modest newsletter.

This week we're on a blogging hiatus, but you can catch up on our ongoing CoVID-19 blog series with: CoVID-19: Visualizing individual patient data. In the latest post we look at how we can use IHME repository of information on 2.3 Million patients around the world to analyze the delay between symptom onset and case confirmation. As always, you can follow along with the GitHub repository containing the respective Python code. We hope you find it useful and gladly welcome any comments you might have.

As we continue our celebration of our 1 year anniversary, we're also proud to announce a new webinar series on Advanced time series analysis, focusing on GARCH models. This is a follow up to our current webinar series on time series analysis that focuses on the ARIMA class models. If you're interested can already sign up for the first edition here. 

In our regularly scheduled programming we look at the St. Petersburg Paradox, have an intro to Web Scraping and Joint Probability Matrices. Finally, we take a first look at pingouin a new Python statistics package.

On the academic front, we consider how Facebook, Twitter and other data troves are revolutionizing social science, a new approach to Learning Causal Models Online by Yoshua Bengio's group, the Economic and social consequences of human mobility restrictions under COVID-19 and Human information processing in complex networks.

Finally, the video of the week we have a Tutorial on Evolutionary Computation and Games by Julian Togelius, Sebastian Risi, and Georgios N. Yannakakis by NYU.

Data shows that the best way for a newsletter to grow is by word of mouth, so if you think one of your friends or colleagues would enjoy this newsletter, just go ahead and forward this email to them and help us spread the word!

Today, more than ever,
Semper discentes,

The D4S team