January 17, 2021

Dear friends,
Welcome to the 86th issue of the Sunday Briefing.

This week we have a double blogging feature. We just published the latest post on the Epidemic Modeling series, ‘Competing CoVID-19 Strains’ where we look at various scenarios of how the introduction of a new more virulent strain (like the UK one) might play out. As always you can find the code in the Epidemiology GitHub.

The second ever post over at Graphs For Data Science is now out: Graphs 101 - A deep look at the airline transportation network. In it we introduce some fundamental graph concepts and definitions in an intuitive way by analyzing a real world dataset You should Subscribe to G4Sci to make sure you never miss a post!

We don’t have a new Causality post, but you can catch up on the Causality Series with our more recent post detailing Inverse Probability Weighing as a technique to facilitate the calculation of the effects of interventions. As usual don’t forget to checkout Causality GitHub repository.

The Jan 27 webinar on “NLP with Deep Learning for Everyone” is filling up quickly but there’s still a few spots available! This will be the first ever edition and you don’t want to miss it!

This week, we explore SQLite as a document database, Medicine’s Machine Learning Problem and the finer points of Trusting machines versus humans. We also take a deep dive into Real World Applications of Markov Decision Process and consider What is PCA?

On the academic front, we have reviews on the efficacy of face masks against COVID-19 and on Convolutional Neural Nets. We also learn how to Map coupled time-series onto a complex network and the Challenges when identifying migration from geo-located Twitter data.

Finally, this week we have our very first ‘Data Science Book ’ highlight: Data Science for Business by Foster Provost and Tom Fawcett. In the video of the week we have an introduction to Twitter Sentiment Analysis Using Python.

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Semper discentes,

The D4S Team