— In the News —
The idea of data "ownership" has many flaws and data "consent" isn't much better. Here's a thoughtful look at the issues and how a "Data Bill of Rights" could be a step in the right direction.
Facial-recognition technology could revolutionize multiple industries and it's advancing much faster than most people realize. This longread in the New Yorker explores how the technology has evolved, where it's going, and the inevitable dangers.
One of the Best Papers from the recent Neural Information Processing Systems conference suggests a redesign to the core machinery of deep learning. Here's an easy to follow explanation of why the technique is useful and how it works.
— Sponsored Link —
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— Tools and Techniques —
A recent panel discussion with Amy Heineike, Paco Nathan, and Pete Warden explored ways that data science and engineering teams work together to build and deploy models. This write-up of the discussion covers collaboration, typical tensions and practical advice for addressing those tensions.
Learn how to collect and analyze social media data using topic models, text networks, and word2vec with this open source version of the Text as Data class from Duke's Data Science program.
This Tips & Tricks article is a well-organized collection of ways to be more productive with Jupyter Notebooks.
Great roundup by Sebastian Ruder of cutting-edge NLP ideas. Each of the 10 ideas presented here includes summaries of key papers and lots of useful links.
The path to success starts with preparation. This prep course teaches data science essentials, including Python, SQL, and machine learning, and prepares students for entrance exams to data science immersives and bootcamps and for participation in Galvanize’s Data Science Immersive.
— Resources —
Geocomputation with R is a new text that covers geographic data analysis, visualization and modeling using R. Starts with the basics needed to understand spatial data and covers a wide range of topics from there. The printed version won't be available until Spring 2019 but the online version is complete and available for free.
— Data Viz —
Small Multiples are a great way to show comparisons. In this article, Peter Bell from the Pew Research Center explores what Small Multiples are, when to use them, and how to use them most effectively.
As the tools and user expectations have evolved, data visualization has changed a lot over the years. In this article, Elijah Meeks explores the next wave of data visualization where modes like notebooks, dashboards and long-form storytelling converge.