Dive into our blog where we turn complex data into clear, actionable insights. Stay tuned for fresh perspectives and expert advice from the heart of Automattic’s data team.
This week, Charles, Xaio, Chris, and Boris share pieces on machine learning, MySQL, pop lyrics, and career advice.
Charles Earl reports on Elfbot, a machine learning project geared to helping Happiness Engineers provide fast, efficient, wonderfully human support to WordPress.com users.
Two great reads and a YouTube channel await you in this installment of “This Week in Data Reading.”
This week, Boris Gorelik shares his thoughts on a NYU study of “The Persuasive Power of Data Visualization.”
Boris Gorelik shows how we use data at Automattic to visualize social connections between Automatticians.
In this week in data reading, Demet offers up some digital anthropology over at FiveThirtyEight while Charles shares two papers he enjoyed in the field of natural language processing, and Carly offers a piece on back propagation.
The WordPress.org plugin directory has been significantly rebuilt over the past year and should go live soon (test site). Many from across the WordPress community helped with this effort. I focused on improving plugin search relevancy. This was a great learning experience on how to build more relevant searches for a couple of reasons: There…
This week, Boris, Demet, Charles, and Sirin offer pieces on data visualization, deep learning architecture, the “Dirtbag Left,” and an obituary for the late Hans Rosling, a man who “had a talent for using numbers to tell exciting stories” — largely about the world becoming a better place. Enjoy our recommendations below and remember to…
Talking with friends last week, many of us sheepishly admitted that we have already “broken” our 2017 resolutions. According to a popularly cited study by Norcross in 2002, only 64% of 150 participants who had made resolutions were able to stick with them beyond a month. A recent Marist poll lists some popular choices for…
This week, Boris and Charles bring you two new resources for data reading and pose some questions for discussion on how you approach scientific literature, and you detect and deal with bias inherent in your applications. Looking forward to your comments!