April 25, 2021

Dear friends,
Welcome to the 100th issue of the Sunday Briefing. Can you believe we’ve been doing this for almost two years!

This week we have a new post over at G4Sci: Graph Components: Strongly and Weakly Connected Components an overview of algorithms to identify connected components and how they can be used to better understand a real world communication network. You should Subscribe to G4Sci to make sure you never miss a post!

Over at Medium, Competing CoVID-19 Strains is the most recent post on the Epidemiology series and Mediation is the latest for the Causality series while we continue to work on the particularly long section 3.8 of the Primer. Finally, As always you can find the code in the Epidemiology and Causality GitHub repos, respectively.

We’re proud to announce two new webinars. June will be dedicated to NLP with Natural Language Processing (NLP) for Everyone on Jun 9 followed by the more advanced NLP with Deep Learning for Everyone on Jun 25.

This week we explore how to select algorithms for time series forecasting, how to use Plotly as Pandas Plotting Backend and a new way to make maps with OpenStreetMap. We also consider opportunities, challenges and design of a Central Bank Digital Currency and Blockchain applications in the United Nations.

From the Ivory Tower, we consider Online Sampling of Temporal Networks, Explicit and implicit network connectivity, Simpson’s Paradox in Covid-19 Case Fatality Rates and Principal Components along Quiver Representation.

Finally, this weeks ‘Data Science Book ’ highlight is “Transformers for Natural Language Processing” by D. Rothman and in the video of the week we cover Forecasting at Scale: How and Why We Developed Prophet for Forecasting at Facebook.

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Semper discentes,

The D4S Team