I am pleased to announce the 0.9.0 release of the data algebra. The data algebra is realization of the Codd relational algebra for data in written in terms of Python method chaining. It allows the concise clear specification of useful data transforms. Some examples can be found here. Benefits include […]
Estimated reading time: 1 minute
Back to teaching. For a few years we’ve been running a data science intensive at for a really neat FAAMG company. The idea is to give engineers some hands on live workbook time using methods varying from linear regression, xgboost, to deep neural networks. Learning how participants progress and internalize […]
Estimated reading time: 1 minute
Our book, Practical Data Science with R, just had its first year anniversary! The book is doing great, if you are working with R and data I recommend you check it out. (link)
Estimated reading time: 22 seconds
I’d like to address how and why I am making the recent light-board video lectures (please check them out: A/B testing and Simpson’s Paradox, and Bayes’s Law and Odds). How How is the easy part. There are a number of tutorials on how to do this. The one I found […]
Estimated reading time: 5 minutes
The core of our “statistics to English translation” series is Nina Zumel’s sequence of articles: “I don’t think that means what you think it means;” Statistics to English Translation, Part 1: Accuracy Measures Statistics to English Translation, Part 2a: ’Significant’ Doesn’t Always Mean ’Important’ Statistics to English Translation, Part 2b: […]
Estimated reading time: 55 seconds
I am working on a promising new series of notes: common data science fallacies and pitfalls. (Probably still looking for a good name for the series!) I thought I would share a few thoughts on it, and hopefully not jinx it too badly.
Estimated reading time: 4 minutes
We have a new R WVPlots plot: ROCPlotPairList. It is useful for comparing the ROC/AUC of multiple models on the same data set. library(WVPlots) set.seed(34903490) x1 <- rnorm(50) x2 <- rnorm(length(x1)) x3 <- rnorm(length(x1)) y <- 0.2*x2^2 + 0.5*x2 + x1 + rnorm(length(x1)) frm <- data.frame( x1 = x1, x2 […]
Estimated reading time: 47 seconds