Reading List

For Pride 2021, a selection of stories on the intersection of data, bias, and LGBTQIA+ communities

There’s a widespread—and understandable—unease about attempts to measure or quantify traits that people have historically associated with marginalized groups. This iffy (or even icky) feeling goes back to the very origins of modern data science, and attempts by 19th-century pseudosciences like phrenology and physiognomy to detect and catalog deviance from…

EXPLORING DATA SCIENCE

Taking a step back from the hum of day-to-day model-training and number-crunching, Phoebe Wong asks some very big questions in her 2019 post about the types of knowledge data scientists explore — and generate. Starting off with the long-simmering tension between models that predict real-world outcomes and those that seek to explain the causal forces at play, Phoebe suggests that we might not be in either/or territory after all: “predictive and causal models serve very different purposes and require very different data and statistical modeling processes, and often we need to do both.”

An accessible, illustrated introduction to a complex topic

In recent years, GANs (generative adversarial networks) have been all the rage in the field of deep-learning generative models, leaving VAEs in relative obscurity. But there’s much to gain from a solid footing in variational autoencoders, which tackle similar challenges but use a different architectural foundation. If you were looking for an engaging, accessible way to learn more about VAEs, Joseph and Baptiste Rocca’s introduction hits the spot. They define terms, walk us through the various elements that make up VAEs and how they relate to each other, and add beautiful illustrations for all the visual learners out there.

Reading List

Discover some of the best Twitter data analyses from the TDS archive.

Anecdotally, it would seem that you can be on Twitter, or you can attempt to find joy, health, and balance in your life, but not both. The writers, journalists, and niche food-opinion-havers in my timeline form a fairly diverse lineup. …

Or is it “chefly” or “cheffily” or “chuffingly”

According to some North American etiquette authorities, it’s acceptable to send newlyweds a gift up to an entire year after the wedding. I remember being floored by this tidbit when I first learned about it many, many years ago, as I grew up in a culture where it would be…

Ben Huberman

Editor in Chief, Towards Data Science. Previously: Editorial lead, Automattic & Senior Editor, Longreads.

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