Have you ever thought R’s approach to machine learning is outdated? Like, data analysis and visualization tools are superb. Everything feels intuitive and every following step of your workflow integrates seamlessly. That’s by design. Or, the design of the tidyverse collection of packages. R tidymodels aims to do ...

Shiny applications are fantastic for turning data into interactive dashboards and web apps, making data exploration and visualization more engaging. But even the most visually appealing Shiny app can hit performance snags. Lagging visualizations, delayed user interactions, and sluggish data updates can quickly turn a promising Shiny app into a ...

We are pleased to announce the full line-up for this year’s Shiny in Production conference! This year, we’re introducing a new lightning talk session. These short 5 minute talks will allow us to showcase many more uses of Shiny in Production. The conference will still feature 6 full length talks, ...

In our last article, we explored the S4 OOP system in R. Up until this point, we had only discussed functional OOP systems in R. Today, we are going to learn about two encapsulated OOP systems available for R: Reference Classes –  introduced to R in 2010 in version 2.12.0 (source). Sometimes also ...

When developing R Shiny apps, making sure they work well and are reliable is important. Rigorous testing isn’t just about finding bugs; it’s about preventing them, saving time, and ensuring everything runs smoothly. We did the comparison of shinytest2 and Cypress. Check out this blog post to learn ...

In this article we look at how to use the MySQL EXPLAIN and EXPLAIN ANALYZE commands to optimise your queries.  We review the syntax these commands use, interpreting their output and how tools like MySQL Workbench and dbForge Studio for MySQL be used in conjunction with them.  To do this ...

The video below shows how to conduct a t-test and an ANOVA analysis using the pingouin library from Python.

Auto XGBoost, Auto LighGBM, Auto CatBoost, Auto GradientBoosting

Ahh, SHAP. As you know it’s become one of the leading frameworks for explaining ML model predictions. I’d guess it’s popularity is due to its appealing theoretical basis, its universal applicability to any type of ML model, and its easy-to-use python package. SHAP promises to turn your ...

Rhino, the R package development framework created by Appsilon, has recently released two updates – versions 1.8 and 1.9. In this fireside chat, Kamil Żyła (one of the core developers of Rhino) and Marek Rogala (Appsilon’s Head of Technology) sit down to discuss these updates and the vision behind Rhino. Watch ...