Are you confused by Bayesian statistics? If you understand Ridge regression, one of the most common Bayesian models is within your reach! This post gives a brief intro to Bayesian thinking and shows you how just how similar Ridge regression is to Bayesian linear regression by walking you through the math and exploring how coefficient estimates from both models compare.
For nearly a whole year, the STATcrew waited for this magic moment: The STATWORX Office Opening! We had a great day at the Soft Opening, with a tour of the office, a town hall meeting and a tasty barbecue with cold beers. Read all about it in this blog post!
In this blog post, Andre explains two approaches on how to secure a REST API: One works with nginx and the sub-request feature, the other implements the verification part in the API itself.
Do you want to visualize beautiful graphs in R but are shy to leave the tidyverse? Tidygraph and Ggraph ‘got you covered! See how their main functionalities are applied in this social network example!
After having successfully run a simple R-script inside a Docker container before, we next attempt to repeat this process for entire apps built within the RShiny framework. Join me on the next step toward deploying your work done in R with the help of neat Docker containers!
How can you frame a data science question according to your client’s needs? In this blog post, our colleague Dominique explains how important it is to think about the business question in a different way – the data science way.
To increase revenue, customers should be offered products they may need or films they might like. In this blog post, our colleague Andreas explains how to train your own movie recommender with R and provides it in a Shiny App.
As data scientists, getting our hands on the data we need is often the most challenging part of a project. In practice, we tend to make life hard on ourselves because we don’t use the best tools for the job. Well no longer! Read on to learn how can you can harness Airflow to orchestrate your own ETL processes like a pro!
Have a look at what my team and I worked on during the Permafrost Hackathon in Zurich. The goal was to detect movements from multitemporal images. Since the images didn’t have any labels, we used unsupervised learning methods. Check it out, yo!
For all those, who are struggling with the (kind of weird) Johns Hopkins University COVID-19 case data CSV files, we’ve created a free API that makes it easy to integrate the latest worldwide COVID-19 data into your application.