January 31, 2021

Dear friends,
Welcome to the Jan 31st issue of the Sunday Briefing.

This week we are happy to announce the most recent post over at Graphs For Data Science: Understanding DBSCAN and K-NN with Random Geometric Graphs. In it we explore the connections between Random Geometric Graphs and the K-Nearest Neighbor and DBSCAN machine learning algorithms. You should Subscribe to G4Sci to make sure you never miss a post!

You can catch up on our recent posts on Competing CoVID-19 Strains and Inverse Probability Weighing and as always you can find the code in the Epidemiology and Causality GitHub repos, respectively.

The first edition of the “NLP with Deep Learning for Everyone” webinar on Jan 27 was a lot of fun with lots of interesting question and discussion. If you’re interested you can also download the slide deck.

This week we cover Twitter’s new approach to academic research with the Twitter API, celebrate the 100 years of the naming of robots, take a look at Plotnine, an implementation of the Grammar of Graphics for Python and Algorithmic Trading with Economics Driven Deep Learning.

From the Ivory Tower we have, a review on Economic complexity theory and applications, a survey on Machine Ethics Implementations and Activation Functions in Artificial Neural Networks.

Finally, this weeks ‘Data Science Book ’ highlight is François Chollet’s “Deep Learning with Python” and in the video of the week, we have a tutorial on GloVe Vectors Embedding with TF 2.0 and Keras.

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Semper discentes,

The D4S Team