Lately I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to tune more complex models. Today, I’m exploring a different part of the tidymodels framework; I’m showing how to implement principal component analysis via recipes with this week’...

I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to tune more complex models. Today, I’m using this week’s #TidyTuesday dataset on beer production to show how to use bootstrap resampling to estimate model parameters. Here is the ...

I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to tune more complex models. Today, I’m using a #TidyTuesday dataset from earlier this year on trees around San Francisco to show how to tune the hyperparameters of a random ...

I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to tune more complex models. Today, I’m using this week’s #TidyTuesday dataset on The Office to show how to build a LASSO regression model and choose regularization parameters! Here ...

I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first getting started to how to tune machine learning models. Today, I’m using this week’s #TidyTuesday dataset on college tuition and diversity at US colleges to show some data preprocessing steps and how to use ...

Last week I published a screencast demonstrating how to use the tidymodels framework and specifically the recipes package. Today, I’m using this week’s #TidyTuesday dataset on food consumption around the world to show hyperparameter tuning! Here is the code I used in the video, for those who prefer ...

Last week I published my first screencast showing how to use the tidymodels framework for machine learning and modeling in R. Today, I’m using this week’s #TidyTuesday dataset on hotel bookings to show how to use one of the tidymodels packages recipes with some simple models! Here is ...

This week I started my new job as a software engineer at RStudio, working with Max Kuhn and other folks on tidymodels. I am really excited about tidymodels because my own experience as a practicing data scientist has shown me some of the areas for growth that still exist in ...

One of the biggest projects I have worked on over the past several years is the Stack Overflow Developer Survey, and one of the most unique aspects of this survey is the extensive salary data that is collected. This salary data is used to power the Stack Overflow Salary Calculator, ...

A paper I worked on was just published in a medical journal. This is quite an odd thing for me to be able to say, given my academic background and the career path I have had, but there you go! The first author of this paper is a long-time friend ...

Today I am happy to announce a new(-ish), free, online, interactive course that I have developed, Supervised Machine Learning: Case Studies in R! ???? Supervised machine learning in R Predictive modeling, or supervised machine learning, is a powerful...

I am so pleased to now be an RStudio-certified tidyverse trainer! ???? I have been teaching technical content for decades, whether in a university classroom, developing online courses, or leading workshops, but I still found this program valuable for my own professonal development. I learned a lot that is going to ...

Today I am so pleased to introduce a new package for calculating weighted log odds ratios, tidylo. Often in data analysis, we want to measure how the usage or frequency of some feature, such as words, differs across some group or set, such as documents. One statistic often used to ...

I recently wrote about the release of tidytext 0.2.1, and one of the most useful new features in this release is a couple of helper functions for making plots with ggplot2. These helper functions address a class of challenges that often arises when dealing with text data, so we’ve included ...

I am an enthusiastic proponent of using tidy data principles for dealing with text data. This kind of approach offers a fluent and flexible option not just for exploratory data analysis, but also for machine learning for text, including both unsupervised machine learning and supervised machine learning. I haven’t ...