Cross-validation is a widely used technique to assess the generalization performance of a machine learning model. In this blog post I will introduce the basics of cross-validation, provide guidelines to tweak its parameters, and illustrate how to build it from scratch in an efficient way.
This blog post looks at how we can improve predictive accuracy by combining forecasts from different models.
Time flies by and we are more people now here at STATWROX. But, did we change our behavior in using emojis or are we still the same? I am revisiting my analysis and will have a look!
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.
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.
Vom 09.-10. Oktober findet die Data University an der Goethe-Uni in Frankfurt statt, präsentiert von STATWORX & BARC.
What are driving factors behind the gas price? With freely accessible data we are goging to find out if the brand, the location and more have any impact on the price!
In time series context, one of most the commonly used measures is the MAPE. In this blog post, I evaluate critical arguments and weaknesses concerning the MAPE and demonstrate alternative measures.
Want to obtain a specific dataset from a website which does not have an API? In this post, I explain how to do this by scraping data using Python, how you determine whether it is allowed to scrape a specific page and more.
Vom 09.-10. Oktober präsentieren wir von STATWORX gemeinsam mit BARC die Data University an der Goethe-Uni in Frankfurt. 2 Tage lang werden wir dort unser geballtes Data Science Wissen in praxisorientierten Workshops an die Teilnehmenden weitergeben. In zwei besonders spannenden Workshops von unserem Kollegen David dreht sich am zweiten Schulungstag alles um das R Paket Shiny. Vormittags wird es eine …