November 22, 2020

Dear friends,
Welcome to the 78th issue of the Sunday Briefing.

This week was heavily Causality focused. On Friday, we taught a short version of the Causality webinar at PyData Global 2020. The live event was recorded and we’ll share the video when it gets posted. We also just published the next post on the Causality series where we cover the ‘Front-door Criterion’ another alternative approach to compute causal effects from empirical data. As always, all the relevant code can be found in GitHub. On the Epidemic Modeling front, you can also checkout the latest blog post where we go over the basics of Network Structure, Superspreaders and Contact Tracing.

This week we analyze Good Data Analysis, how we can turn Metadata Into Insights with Databook, Gödel’s First Incompleteness Theorem, How Prediction Markets Beat Polls and The state of the AWK (the most useful programming language you never heard of).

On the academic front, we have surveys on the Explainability of Supervised Machine Learning and Centrality Measures in Complex Networks. We also analyze the growth equation of cities and the scales of human mobility.

Finaly, in the video of the week we have an Introduction to Machine Learning by Eric Grimson from MIT.

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Semper discentes,

The D4S Team