November 8, 2020

Dear friends,
Welcome to the 76th issue of the Sunday Briefing.

We are proud to announce that we are successfully keeping a more regular blogging schedule with the publication of the latest blog post in the Causality series were we cover ‘The Backdoor Criterion’, the way in which we can calculate causal effects directly 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.

We would also like to highlight this weeks edition of the revamped [Data Visualization with Matplotlib and Seaborn](Data Visualization with matplotlib and seaborn for Everyone), now with new Seaborn material. There are still some slots open but they’re filling out fast!

This week we have an AI Expert Roadmap, a look at how to use LIME to explain ML Classifiers and a wonderful visualization to help us Understanding Statistical Power and Significance Testing.

On the academic front, we explore some lesser known algorithms with an overview of swarm intelligence-based algorithms for numerical association rule mining and Algorithms for Causal Reasoning in Probability Trees. We consider Random walk with memory on complex networks and how to Navigate the landscape of multiplayer games and How to (seriously) read a scientific paper.

Finaly, in the video of the week we have an OpenCV tutorial in Python.

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Semper discentes,

The D4S Team