ISSUE 293 ·   July 7, 2020        

I've been on several live seminars recently and have been impressed with how useful they've been. It's got me thinking that it could be worth hosting live calls with some of the authors and project leads that are featured in Data Elixir. Authors could go deeper into a topic, offer perspectives about where things are going, include live Q/A, etc. If that sounds interesting, sign up here >>

In the News

A guide to R — the pandemic’s misunderstood metric

In spite of its widespread use in the media, epidemiologists have been keen to downplay the importance of the reproduction number known as "R". In this article in Nature, David Adam explores what that number really means and what we should be watching instead.
Nature

Who Is Responsible When Autonomous Systems Fail?

When a self-driving Uber car struck and killed a pedestrian in 2018, the company was cleared of criminal wrongdoing, but the human tasked with monitoring the system faces the prospect of manslaughter charges. The outcome could be a harbinger of what lies ahead.
CIGI Online

Tools and Techniques

Reflecting on a year of making ML actually useful

After her first year as a machine learning engineer, Shreya Shankar offers real-world insights into the field and why most machine learning projects don't make it to production — in spite of "crazy advances" in machine learning technology and expertise.
Shreya Shankar

Shopify's Data Science & Engineering Foundations

Shopify's Data Team is building for the long term and it's paying off. Here's how they leverage years of work in data warehousing and analysis to support its ecosystem of internal teams and partners.
Shopify Engineering Blog

Paper Projects

Paper Projects provides a structure to implement experiments and learn from trending papers. It's intended to be an "opportunity for the community to come together, learn and help each other."
Made with ML

How to Set Up a Python Project For Automation and Collaboration

Great guide for setting up a new Python project with an automated workflow of units tests, coverage reports, lint checks, and type checks that’ll catch the the majority of errors and facilitate collaboration.
Eugene Yan

Resources

learnR4free 🔖

This is easily the best collection of free R learning resources I've come across. There's a wide variety of topics here, including getting-started guides, statistics, machine learning, text mining, package development, efficient programming, ggplot2, etc. For all levels, beginner to advanced.
learnr4free | curation by Mine Dogucu

The Analytics Setup Guidebook

This short book explores the options for building analytics and BI stacks for the modern cloud. It's a very well-written, practical tour that walks through the various components and how they fit together. Great read.
holistics

Data Viz

Interactive, Scalable Dashboards with Vaex and Dash

Vaex and Dash are open-source libraries that make it easy to build interactive dashboards on the web for millions, and even billions, of data samples using just your Python skills. This tutorial shows what you can do with these libraries and how to use them.
Plotly Blog

The Case Against Dashboards

COVID-19 data has largely been a success story for data visualization but there are important lessons to be learned. Detailed dashboards, in particular, can be problematic and misleading. This short post outlines some of the key issues, including suggestions for better approaches.
Visualization Design Lab, University of Utah

Job Board

New on the Job Board:

• Database Analyst at Transformation Church (border of NC/SC, US)
• Director of Data Science at UnitedHealth Group (remote)
• Senior Data Product Manager (New York, Chicago)
• Staff Data Scientist at Twitter  (remote)

Check these out and more >>

Data Elixir is curated and maintained by Lon Riesberg. If you need help on a data project or have a suggestion for the newsletter, reply back to this email or grab a spot on my calendar >>