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Issue #40

Mar 01, 2020

Dear friends,

Welcome to the fortieth edition of the Sunday Briefing. Just a dozen more before we can celebrate our first anniversary! 

This week we shift gears slightly to look more deeply at an often overlooked skill in your data science toolkit, visualization. We start with an overview on how to produce good and informative maps in ArcGIS latest blog post, Mapping coronavirus, responsibly a look at Sorting Networks and other more Unique Visualizations and a finally framework for Data visualization literacy

We also have some mathematics book recommendations for the adventurous self-learner, a survey of Mobility Analyses, a look at the Emerging Landscape of Explainable AI and answer the age old question of How To Avoid Being Eaten By a Grue in an academic paper analysis exploration strategies.

Furthermore, we kindly remind you that we are putting together a free full day tutorial on March 7 and would love to see you there. The topic is  Time Series Modeling: ML and Deep Learning Approaches with Python and it will be hosted by good folks over at the NYC offices of Farfetch  and organized by the new NYC URGs and Allies in Data Science Meetup and NYC PyLadies.

Finally, in the video of the week we take a deep dive into Python Data Visualization With Bokeh, a powerful Python based package for interactive web visualizations.

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!

Semper discentes,

The D4S team

Blog:

Our latest post 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:
1.2 - Simpson's Paradox
1.3 - Probability Theory and Statistics

GitHub: github.com/DataForScience/Causality

Top Links:

Tutorials and blog posts that came across our desk this week.
  1. Mapping coronavirus, responsibly [esri.com/arcgis-blog]
  2. Mathematics for the adventurous self-learner [neilwithdata.com]
  3. Pycel: Compiling Excel spreadsheets to Python and making pretty pictures [dirkgorissen.com]
  4. Modern Data Lakes Overview [developer.sh]
  5. Introduction To Sorting Networks [hoytech.github.io]
  6. Musicians Algorithmically Generate Every Possible Melody, Release Them to Public Domain [vice.com]
  7. Getting Familiar with Unique Visualizations! [medium.com/sfu-big-data]

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.


Python Data Visualization With Bokeh
 

https://www.youtube.com/watch?v=2TR_6VaVSOs

Upcoming Events:

Opportunities to learn from us
  1. Mar 7, 2020Time Series Modeling: ML and Deep Learning Approaches with Python [Register]  🆕
  2. Mar 9, 2020Data Visualization with matplotlib and seaborn [Register
  3. Mar 15-16, 2020 - Time series modeling: ML and deep learning approaches - Strata/AI [Register
  4. Mar 27, 2020Deep Learning for Everyone [Register
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Publishes on Sunday.
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