Fresh data insights from Automattic.
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.
-
Looker NYC Meetup
Like any company, Automattic is constantly on a journey to get better: sometimes we have the good fortune of finding improvement in leaps and bounds, but most of the time, we move slowly, we make small changes, finding iterative wins and moving down the to‑do list. I think probably this is how most progress happens:…
-
This Week in Data Reading: Experimentation, Tech and the Humanities, and Eliminating Bias in Testing
This week, Carly, Demet, and Charles bring you some interesting material on tech and the humanities, experimentation culture, and eliminating bias in testing.
-
The 2019 Fairness, Accountability, and Transparency Conference
Charles Earl shares what he learned from this year’s conference.
-
This Week In Data Reading: MOOCs, Collusion in Artificial Intelligence, and Fake News
This week, Boris, Xiao, and Carly share recent reads about MOOCs, collusion in AI pricing, and generating fake news with artificial intelligence.
-
How to Increase Retention and Revenue in 1,000 Nontrivial Steps
Yanir reflects on how data scientists at Automattic work to improve customer retention.
-
Building Thousands of Reproducible ML Models with pipe, the Automattic Machine Learning Pipeline
Demet takes you deep into pipe, a tool that allows anyone at Automattic to build solid machine learning models.
-
Missed Opportunities for Using Text in Data Visualization
Richard Brath talks to Automattic data visualization enthusiasts about the power of text in conveying the results of data science.
-
Links Worth Sharing: What Makes People Successful
Boris shares a paper and a podcast all about the science of success.
-
Introducing pipe, The Automattic Machine Learning Pipeline
Demet gives us an overview of pipe, Automattic’s machine learning pipeline.
-
Links Worth Sharing: The Training and Security of Neural Networks
This week, Charles shares a couple of talks he enjoyed on neural networks at Georgia Tech’s Theoretical Foundation of Deep Learning conference.
