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 …
Do you want to optimise your code but don’t know where to start? In this post I guide you through my thought process when I optimised my code.
A walk through how networks are visualized at STATWORX using the package visNetwork.
In our series of explaining method in 100 lines of code, we tackle random forest this time! We build it from scratch and explore it’s functions.
Is it cheaper to fill up your gas tank in the evening? Many car drivers have their own theories and myths about refuelling. Our colleague Jakob tackled 6 of these myths using statistics in his latest blog post.
Data Science Einsteiger stehen immer wieder vor der gleichen Frage: Welche Programmiersprache sollte man als Erstes lernen? Die Wahl fällt meistens auf eine der beiden großen Anbieter, R oder Python. Mit diesem Blogartikel wollen wir bei der Suche nach der geeigneten Programmiersprache helfen.
We at STATWORX use mostly R or Python for our projects. But why not both? With the help of the reticulate package we can use Python within R. Here we show an example of how to train a Support Vector Machine.
This blogpost explains step by step how you can build your own Docker Image and include R scripts. With this you can have scripts running at every image’s beginning.
It’s Valentine’s day, making this the most romantic time of the year. But actually, already 2018 was a year full of love here at STATWORX: many of my STATWORX colleagues got engaged. And so we began to wonder – some fearful, some hopeful – who will be next? Therefore, today we’re going to tackle this question in the only true way: with data science!
In this blog we will explore the plotly library for python and R. We show how plotly is structured and use the LA Metro Bike dataset as an example to create interactive plots.