Dynamic UI Elements in Shiny

Oliver Guggenbühl Blog, Data Science

Shiny enables its users to quickly create a fixed UI with code. Although simple, this can prove to be quite limiting. Applying the principles of reactivity to the UI part of a ShinyApp is a natural progression from reactive coding as we know it already from Shiny’s server side. This blog entry reviews and discusses two of the most convenient tools for doing so.

learn R or Python

R or Python

Fran Peric Blog

Data Science beginners often encounter the same question: which programming language should one learn first? The choice usually falls on one of the two major providers, R or Python. With this blog article, we want to help you with the search for the right programming language for you.

checking prediction

Revisited: Forecasting Last Christmas Search Volume

Sebastian Heinz Blog, Data Science

It is June and nearly half of the year is over, marking the middle between Christmas 2018 and 2019. Last year in autumn, I’ve published a blog post about predicting Wham’s “Last Christmas” search volume using Google Trends data with different types of neural network architectures. Of course, now I want to know how good the predictions were, compared to …

Simulating the bias-variance tradeoff in R

Robin Kraft Blog, Data Science, Statistik

In my last blog post, I have elaborated on the Bagging algorithm and showed its prediction performance via simulation. Here, I want to go into the details on how to simulate the bias and variance of a nonparametric regression fitting method using R. These kinds of questions arise here at STATWORX when developing, for example, new machine learning algorithms or …