One of the biggest problems of the COVID-19 pandemic is that there are no reliable numbers of infections. This fact renders many model projections next to useless. If you want to get to know a simple method how to roughly estimate the real number of infections and expected deaths in ... [Read more...]

Learning Machines proudly presents a guest post by Martijn Weterings from the Food and Natural Products research group of the Institute of Life Technologies at the University of Applied Sciences of Western Switzerland in Sion. The topic of this post will be the fitting with the R-package optim. Food? That ... [Read more...]

Correlation and its associated challenges don’t lose their fascination: most people know that correlation doesn’t imply causation, not many people know that the opposite is also true (see: Causation doesn’t imply Correlation either) and some know that correlation can just be random (so-called spurious correlation). If you ... [Read more...]

It is such a beautiful day outside, lot’s of sunshine, spring at last… and we are now basically all grounded and sitting here, waiting to get sick. So, why not a post from the new epicentre of the global COVID-19 pandemic, Central Europe, more exactly where I live: Germany?! ... [Read more...]

Valentine’s Day is around the corner and love is in the air… but, shock horror, nearly every second marriage ends in a divorce! Unfortunately, I can tell you first hand that this is an experience you’d rather not have. In this post, we see how data science, in ... [Read more...]

A new invisible enemy, only 30kb in size, has emerged and is on a killing spree around the world: 2019-nCoV, the Novel Coronavirus! It has already killed more people than the SARS pandemic and its outbreak has been declared a Public Health Emergency of International Concern (PHEIC) by the World ... [Read more...]

We have all watched with great horror the catastrophic fires in Australia. Over many years scientists have been studying simulations to understand the underlying dynamics better. They tell us, that “what Australia needs is more fires, but of the right kind”. What do they mean by that? One such simulation ... [Read more...]

We already covered the so-called Accuracy-Interpretability Trade-Off which states that oftentimes the more accurate the results of an AI are the harder it is to interpret how it arrived at its conclusions (see also: Learning Data Science: Predicting Income Brackets). This is especially true for Neural Networks: while often delivering ... [Read more...]

Learning Machines proudly presents a fascinating guest post by decision and risk analyst Robert D. Brown III with a great application of R in the business and especially startup-arena! I encourage you to visit his blog too: Thales’ Press. Have fun! Introduction While Excel remains the tool of choice among ... [Read more...]

Happy New Year to all of you! 2020 is here and it seems that we are being overwhelmed by more and more irrationality, especially fake news and conspiracy theories. In this post, I will give you some indication that this might actually not be the case (shock horror: good news alert!). ... [Read more...]

After my little rant (which went viral!) about the tidyverse from last week, we are going to do a little fun project in the 50’th ???? post of this blog: ASCII Art! If you want to have some fun by painting with letters (i.e. ASCII characters) in R and get ... [Read more...]

There seems to be some revolution going on in the R sphere… people seem to be jumping at what is commonly known as the tidyverse, a collection of packages developed and maintained by the Chief Scientist of RStudio, Hadley Wickham. In this post, I explain what the tidyverse is and ... [Read more...]

Modern movies use a lot of mathematics for their computer animations and CGI effects, one of them is what is known under the name fractals. In this post, we will use this technique to create islands with coastlines that look extraordinarily realistic. If you want to do that yourself read ... [Read more...]

As we have already seen in former posts simple methods can be surprisingly successful in yielding good results (see e.g Learning Data Science: Predicting Income Brackets or Teach R to read handwritten Digits with just 4 Lines of Code). If you want to learn how some simple mathematics, known as ... [Read more...]

Data Scientists know that about 80% of a Data Science project consists of preparing the data so that they can be analyzed. Building Machine Learning models is the fun part that only comes afterwards! This process is called Data Wrangling (or Data Munging). If you want to use some Base R ... [Read more...]

It has been an old dream to teach a computer to see, i.e. to hold something in front of a camera and let the computer tell you what it sees. For decades it has been exactly that: a dream – because we as human beings are able to see, we ... [Read more...]

Customer Relationship Management (CRM) is not only about acquiring new customers but especially about retaining existing ones. That is because acquisition is often much more expensive than retention. In this post, we learn how to analyze the reasons of customer churn (i.e. customers leaving the company). We do this ... [Read more...]

In 1965 the University of Chicago rejected Kurt Vonnegut’s college thesis, which claimed that all stories shared common structures, or “shapes”, including “Man in a Hole”, “Boy gets Girl” and “Cinderella”. Many years later the then already legendary Vonnegut gave a hilarious lecture on this idea – before continuing to read ... [Read more...]

By now you will know that it is a good tradition of this blog to explain stuff by rebuilding toy examples of it in R (see e.g. Understanding the Maths of Computed Tomography (CT) scans, So, what is AI really? or Google’s Eigenvector… or how a Random Surfer ... [Read more...]

Today the biggest book fair of the world starts again in Frankfurt, Germany. I thought this might be a good opportunity to do you some good! Springer is one of the most renowned scientific publishing companies in the world. Normally, their books are quite expensive but also in the publishing ... [Read more...]