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 […]
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 […]
Nina and I are excited our book is one of the 16 titles featured in the Math for Programmers bundle on @humble! This bundle delivers the critical #math and #algorithms skills needed for careers in #programming and #datascience. Pay what you want & support #charity. https://www.humblebundle.com/books/math-for-programmers-manning-publications-books
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)
I’d like to share an introduction to my data science chalk talk series (video link, series link)
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 […]
An update on site maintenance. We have moved the Win Vector LLC site to https hosting. Some links were damaged by the transition, but we are fixing them as we find them. Overall the following changes are present: http://win-vector.com/dfiles/ file content has moved to https://github.com/WinVector/Examples/tree/main/dfiles The blog is here: https://win-vector.com/blog-2/. […]
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: […]
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.
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 […]