Posts tagged "Python"

Really Fast Bayesian Linear Regression

A little performance vignette. I measured the draw and update of a Bayesian linear regression against how fast one core can actually go, and found which scipy routines get there and which don’t.

Churn Risk Is a Conditional Rate: A Simpler Empirical Bayes Model

My old churn model measured how surprising a user’s silence was against their own history. That’s a real question with a real answer, but it isn’t churn risk: it flagged regulars who took a week off and ignored light users who’d quietly stopped. It passed every backtest for two years; a confused user in a focus group is what caught it. The replacement is the table banks use for late accounts – bin users by how long they’ve been gone and how much they normally use the product, count who came back – with the same empirical Bayes shrinkage as before, pointed at the right quantity this time.

Building systemd Portable Service Images for Python Apps with Native Dependencies

In my previous post, I covered running portable services—version-controlled config, atomic updates, zero-downtime restarts, all without a container runtime. This is only half of the container story, though. You also need to build the service images.

An Empirical Bayes Approach to Churn Estimation

Update, August 2026: I no longer stand behind this approach. The model below measures how surprising a user’s silence is against their own history, and in production that turned out to flag the users least likely to leave. I’ve written up what went wrong and what replaced it in Churn Risk Is a Conditional Rate. The original post is left as written.

Use Exact Tests for Nested Experimental Designs

A Motivating Example

We were studying how microglia affect neuronal networks using a standard imaging experiment: 3 mice, 3 coverslips per condition, about 20 neurons measured per coverslip. Our question: Does LPS activation significantly increase PNA signal?