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Issue #58

Jul 05, 2020

Dear friends,

Welcome to the 4th of July weekend edition of the Sunday Briefing.

This week we're on hiatus from blogging but you can check out our latest blog post in the CoVID-19 series on the blog: CoVID-19: The first truly global event. In this post we take a look at the impact that CoVID-19 has in our lives, economies and societies. As always, you can follow along with the GitHub repository containing the respective Python code. We hope you find it useful and gladly welcome any comments you might have.

We're also happy to announce a partnership with the wonderful people of Data Umbrella. This week we  would like to highlight two of their upcoming online events: Intro to Terminal Commands (Jul 10) and Build a Career in Data Science (Jul 14). Don't miss them!

This week we split our focus into two main topics. On one hand, we take a deep dive into neural networks with an exploration of What is a Convolutional Neural Network? and an interview of Kai-Fu Lee on  the Art of AI,  a discussion on how Neurons that fire together, wire together and a paper on how to generate Synthetic Data for Deep Learning. On the other, we look at Causality with an explanation of Counterfactual Theories of Causation using causality for Interpretable Machine Learning and X-SHAP: towards multiplicative explainability of Machine Learning.

Finally, the video of the week we have a Fire side change with Alan Wilson, Theresa-Marie Rhyne and Julia Krolik on the Color Theory, possibly one the most overlooked ingredients to making a successful visualization.

Data shows that the best way for a newsletter to grow is by word of mouth, so if you think one of your friends or colleagues would enjoy this newsletter, just go ahead and forward this email to them and help us spread the word!

Today, more than ever,
Semper discentes,

The D4S team

Blog:

Our latest blog post in the CoVID-19 series, 'CoVID-19: The first truly global event' takes a look at the impact that the pandemic is having in our lives, economies and societies. As usual, all the code is available in GitHub: github.com/DataForScience/Epidemiology101

The latest post in the Causality series covers the first part of section 1.3 Probability Theory and Statistics, an overview of some of the fundamental theoretical requirements for the journey ahead. The code for each blog post in this series is hosted by a dedicated GitHub repository for this project: github.com/DataForScience/Causality

Blog Posts:
Epidemic Modeling:

Causality:
 

Top Links:

Tutorials and blog posts that came across our desk this week.
  1. What is a Convolutional Neural Network? [poloclub.github.io]
  2. The Art of AI: An interview with Kai-Fu Lee [news.cgtn.com]
  3. Counterfactual Theories of Causation [plato.stanford.edu]
  4. Neurons that fire together, wire together… Ok, but how? [dissociativediaries.com]
  5. Democratizing Kaplan-Meier [medium.com/harrys-engineering]
  6. Why Statistics Don’t Capture The Full Extent Of The Systemic Bias In Policing [fivethirtyeight.com]
  7. The Tricky Math of Herd Immunity for COVID-19 [quantamagazine.org]

Fresh off the press:

Some of the most interesting academic papers published recently.

Video of the week:

Interesting discussions, ideas or tutorials that came across our desk.


Color Theory - DVS Fireside Chat

https://www.youtube.com/watch?v=ihy3ENb89EU

Upcoming Events:

Opportunities to learn from us:
  1. Jul 29, 2020Time Series for Everyone [Register
  2. Aug 12, 2020 - Advanced Time Series for Everyone [Register] 🆕 
  3. Aug 21, 2020 - Probability Theory for Everyone [Register] 🆕 
Partner events:
  1. Jul 10, 2020 Intro to Terminal Commands
  2. Jul 14, 2020Build a Career in Data Science
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