— Insight —
Here we are, in the middle of a pandemic, staring out our living room windows like aquarium fish. The question on everybody’s minds: How bad will this really get?
Just 3 months ago, the New York Times published an alarming story about cell phone privacy called, "One Nation Tracked." Now, in the face of a pandemic, there's talk of using our phones to track who we cross paths with. To help make sense of the issues, this article walks-through the variety of ways that cell phone tracking works, how the data is stored, who has access to it, and what's worth being concerned about.
— Tools and Techniques —
This review paper explores motivations, capabilities, and shortcomings of the Julia programming language. If you're interested in Julia but haven't spent much time with it, this is a worthwhile starting point.
Jupyter gets a visual debugger! This announcement on the Jupyter blog walks-through the initial capabilities and where it's going.
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— Resources —
This new Stanford course will introduce the epidemiology and biology of the COVID-19 virus and will investigate it using data science and machine learning tools. A lot of the course material, including lecture videos, are planned to be posted on the course website for non-Stanford students. Starts April 10.
Awesome resource for COVID-19 data in the United States. Includes easily consumed data for each state, links to the best data sources for each state, data quality grades, historical data, a best practices guide, and links to key news items. If you're doing anything with U.S. COVID-19 data, this site is worth having on your shortlist to watch.
An exhaustive list of text summarization papers from 8 top conferences in the last eight years. Includes a breakdown of essential concepts over time, must-read papers, links to key datasets, and a paper retrieval system that makes it easy to find papers via a variety of search criteria.
— Data Viz —
This collection of short interviews offers an inside look at the world of technical freelancing. The vehicle here is data visualization but the insights go far beyond. "There is a big gap of resources explaining how people do what they love." If you've ever thought about going out on your own, this article helps fill that gap.
Great introduction to ggplot2 by Thomas Lin Pedersen, one of the library's key maintainers. This first part of a 2-part series explores the underlying theory of ggplot2 and how that's reflected in the API. Part 2 will focus on extending ggplot2 with practical examples and will be taught live, online, on April 2nd. Follow the links for details.