Machine learning, text analysis, and more
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 is the code I used in the video, for those who prefer reading instead of or in addition to video.
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 resampling! Here is the code I used in the video, for those who prefer reading instead of or in addition to video.
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 reading instead of or in addition to video. Explore the data Our modeling goal here is to predict which countries are Asian countries and which countries are not, based on their patterns of food consumption in the eleven categories from the #TidyTuesday dataset.
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 the code I used in the video, for those who prefer reading instead of or in addition to video.
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 open source software when it comes to modeling and machine learning. Almost nothing has had the kind of dramatic impact on my productivity that the tidyverse and other RStudio investments have had; I am enthusiastic about contributing to that kind of user-focused transformation for modeling and machine learning.