Machine learning is great, until you have to explain it. Thank god for modelStudio. modelStudio is a new R package that makes it easy to interactively explain machine learning models using state-of-the-art techniques like Shapley Values, Break Down pl...

I’m super impressed by the radiant R package. With no prior experience with radiant, I was able to complete a short business analytics report in under 10-minutes. R-Tips Weekly This article is part of R-Tips Weekly, a weekly video tutorial that shows...

I’m super excited to introduce portfoliodown, a new R package that makes it painless for data scientists to create a polished professional website so they can host their project portfolios, get great job interviews, and launch their data science career...

I’m SUPER EXCITED to show fellow time-series enthusiasts a new way that we can scale time series analysis using an amazing technology called Spark! Without Spark, large-scale forecasting projects of 10,000 time series can take days to run because of long-running for-loops and the need to test many models on ...

The ggplot2 package is an essential tool in every data scientists toolkit. Today we show you how to use ggplot2 to make a professional heatmap that organizes customers by their sales purchasing habits. R-Tips Weekly This article is part of R-Tips Wee...

Parallel processing in the tidyverse couldn’t be easier with the furrr package. If you are familiar with the purrr::map() function, then you’ll love furrr::future_map(), which we’ll use in this FREE R-Tip training to get a 2.6X speed-up in our code. R...

Iteratively forecast with tidyverse nested modeling Why is nested forecasting important? For starters, the ability to iteratively forecast time series with many models that are trained on many individual groups has been a huge request from student...

A Lollipop Plot shows the relationship between categories using a dot and a line that connects to a baseline (similar to a Bar Plot). In this short tutorial, we use ggalt to create a Lollipop Plot with the geom_lollipop() function. R-Tips Weekly This...

ggalt is a ggplot2 extension that adds many new ggplot geometries. In this tutorial, we’ll learn how to make dumbbell plots for visualizing change within our data using geom_dumbbell(). R-Tips Weekly This article is part of R-Tips Weekly, a weekly vi...

The ggforce package is a ggplot2 extension that adds many exploratory data analysis features. In this tutorial, we’ll learn how to make hull plots for visualizing clusters or groups within our data. R-Tips Weekly This article is part of R-Tips Weekly...

The ggdist package is a ggplot2 extension that is made for visualizing distributions and uncertainty. We’ll show see how ggdist can be used to make a raincloud plot. R-Tips Weekly This article is part of R-Tips Weekly, a weekly video tutorial that sh...

Spending too much time on making iterative forecasts? I’m super excited to introduce the new panel data forecasting functionality in modeltime. It’s perfect for forecasting many time series at once without for-loops saving you time ⏱️ and aggravation ?. Just say NO to for-loops for forecasting. Fitting many time series ...

Easystats performance is an R package that makes it easy to investigate the relevant assumptions for regression models. Simply use the check_model() function to produce a visualization that combines 6 tests for model performance. We’ll quickly: Lea...

👉 Sign Up For More Blog Articles 👈 Updated July 2021 Both R and Python are great. We’ll showcase some of the strengths of each language in this article by showcasing where the major development efforts are within each ecosystem. ...

A gentle introduction to our forecasting package, modeltime. Modeltime extends the Tidymodels ecosystem for time series forecasting. Learn how to forecast with ARIMA, Prophet, and linear regression time series models in this short video tutorial. ...

The plotnine library is a powerful python visualization library based on R’s ggplot2 package. In this tutorial, we show you how to make a great-looking correlation plot using pandas and plotnine. This article is part of Python-Tips Weekly, a bi-we...

Speed up forecasting with modeltime’s new built-in parallel processing. Fitting many time series models can be an expensive process. To help speed up computation, modeltime now includes parallel processing, which is support for high-performance computing by spreading the model fitting steps across multiple CPUs or clusters. Highlights We now ...

This article is part of R-Tips Weekly, a weekly video tutorial that shows you step-by-step how to do common R coding tasks. Here are the links to get set up. ? Get the Code YouTube Tutorial grafify Video TutorialFor those that prefer Fu...

This article is part of Python-Tips Weekly, a bi-weekly video tutorial that shows you step-by-step how to do common Python coding tasks. Here are the links to get set up. ? Get the Code YouTube Tutorial Siuba Video TutorialFor those tha...

This article is part of R-Tips Weekly, a weekly video tutorial that shows you step-by-step how to do common R coding tasks. Here are the links to get set up. ? Get the Code YouTube Tutorial What is gghalves? gghalves is a new R package...