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: https://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 […]
I would like to re-share links to our free vtreat data preparation system introduction videos, which show you what sort of machine learning problems vtreat can help you with. Python vtreat introduction video (PyData LA 2019), slides here. R vtreat introduction video (Why R? Foundation). The idea is: instead of […]
I’d like some feedback on a possible article or series. I am thinking about writing and/or recording videos on the measure theoretic foundations of probability. The idea is: empirical probability (probabilities of coin flips, dice rolls, and finite sequences) is fairly well taught and approachable. However, theoretical probability (the type […]
