Next Newsletter

Part 1

Learn how to tune hyperparameters for a random forest model, using #TidyTuesday data on food consumption around the world. You can check out the code here on my blog: https://juliasilge.com/blog/food-hyperparameter-tune/

Rising carbon dioxide and the slump in the pound have been frequently graphed. Now we’ve turned the data and graphs into audio

:earth_americas: An R package for spatial and spatiotemporal GLMMs with TMB - GitHub - pbs-assess/sdmTMB: An R package for spatial and spatiotemporal GLMMs with TMB

The gtrendsR package is an R package that can be used to programmatically gather and display Google trend information.

I'm super excited to introduce a new R package that makes it painless for data scientists to create a professional.

A holdout sample is a critical component of a sound time series forecasting methodology. Use to test model forecast error and bias.

Which skills are important to becoming a data scientist? How to pick a language? How to learn the skills? These questions and many more are answered in this post.

Reshaping and navigation commands for R code. Contribute to lionel-/codegrip development by creating an account on GitHub.

The best in visual storytelling

The world population just hit a record. Here's where you fit in and how the world's demographics are expected to change.

From food to gadgets to sports, explore how the business empire of one of the world’s richest men touches the everyday lives of millions in India.

📜 Discover and install useful RStudio addins . Contribute to daattali/addinslist development by creating an account on GitHub.

This learning journey will teach you how to create innovative solutions for complex problems with Machine Learning on Azure in 4 short weeks. With just an hour each day - think coffee-fueled morning ritual or mid-afternoon break - you’ll be able to collaborate and build models faster with the ...

'ggplot2' Based Publication Ready Plots. Contribute to kassambara/ggpubr development by creating an account on GitHub.

Packages used for this chapter: arules (Hahsler et al. 2021), arulesViz (Hahsler 2021b), mlbench (Leisch and Dimitriadou. 2021), tidyverse (Wickham 2021c) You can read the free sample chapter from...

Interactive data tables for R, based on the React Table JavaScript library. Provides an HTML widget that can be used in R Markdown or Quarto documents, Shiny applications, or viewed from an R console.

New psychology findings suggest that attractive students earn higher grades in school, but for female students, this beauty premium disappears when classes are taught remotely. The findings were published in the journal Economic Letters. ...

Weekly bite-sized tips on DataViz, Shiny and Stats/Machine Learning.

Useful function from unheadr for data cleaning

(Cross posted from my blog) Sharing notebooks is harder than it should be. You are working on a notebook (in Jupyter, RStudio, Visual Studio Code, whatever), and want to share it quickly with someone. Maybe you want some feedback, or you’re demonstrating a technique, or there is a cool result you want to quickly show someone. A million reasons to want to quickly share a notebook, but unfortunately there isn’t a quick enough and easy enough solution right now. That’s why I built notebookshari...

Daylight Saving Time may have given us more time to enjoy late-time summer activities, but it can have a negative impact on our health.

This notebook is a starting point for processing tweets from your twitter archive which you can download here. We use a local file input so your data doesn't get uploaded anywhere and stays private. Inspired by Benjamin Schmidt's Working with Twitter exports. Choose your file Select `tweets.js` in the data folder of the unzipped archive to see it visualized below. (This file does not get uploaded anywhere, see source code.) You have tweeted times since Here is a table of all your tweets and the available