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What We’re Reading June 2020

By Jitendra Subramanyam | June 11, 2020 | 0 Comments

Move over ‘data visualization.’ The era of data simulation is here.

These experiences unfold as stories in their own way, and stories are sticky, memorable, and invoke a sense of empathy with the characters when told well. In these simulations, we get to place ourselves in the role of the protagonist, and our community becomes the cast of characters, often simplified into little animated dots or icons on a screen.

Accessible data viz is better data viz

Inclusive design principles and accessibility (often posted about with the tag #a11y) are important to take into consideration when designing data visualization because they help a broader audience understand your graphic. Designing with accessibility in mind can even help make your visualizations easier to understand for people without disabilities.

A Dramatic Tour through Python’s Data Visualization Landscape

The conceit of this post will be: “You need to do Thing X. How would you do Thing X in matplotlib? pandas? Seaborn? ggplot? Altair?”  By doing many different Thing X’s, we’ll develop a reasonable list of pros, cons, and takeaways — or at least a whole bunch of code that might be somehow useful.

Machine Learning Works–It Just Doesn’t Look Like Cyborgs

These aren’t examples of artificial general intelligence, but they are the flagship products of the most valuable companies in the world, and they all rely on state-of-the-art machine learning. We are a ways away from Westworld-esque artificial intelligence, but a world in which machine learning dominates software is not science fiction—it’s the nature of our reality.


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