November 15, 2020

Dear friends,
Welcome to the 77th 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.

We would also like to highlight the coming Live Webinar on Using Streamlit for Data Science organized by our partners at Data Umbrella.

This week we focus on some of the mathematical fundamentals underlying Data Science with a collection of excellen Online Math Notes and an Introduction to Linear Algebra for Applied Machine Learning. We also have some advise on best practices for Data Organization in Spreadsheets and Guidelines for Complex Applications.

On the academic front, we have a paper on DoWhy: An End-to-End Library for Causal Inference by Microsoft, a look at the Statistical physics of complex information dynamics and A Theory of Universal Learning.

Finaly, in the video of the week we have a look at Interpreting ML models with explainable AI by the good folks at the Google Cloud Platform.

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Semper discentes,

The D4S Team