In one of my most popular posts So, what is AI really? I showed that Artificial Intelligence (AI) basically boils down to autonomously learned rules, i.e. conditional statements or simply, conditionals.
In this post, I create the simplest possible classifier, called ZeroR, to show that even this classifier can achieve surprisingly high values for accuracy (i.e. the ratio of correctly predicted instances)… and why this is not necessarily a good thing, so read on!
Continue reading “ZeroR: The Simplest Possible Classifier… or: Why High Accuracy can be Misleading”
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 the form of the
OneR package and an interesting new data set, might potentially help you to avoid that tragedy… so read on!
Continue reading “The One Question you should ask your Partner before Marrying!”
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 with a very convenient point-and-click interface for doing data science on top of R, so read on!
Continue reading “Data Science on Rails: Analyzing Customer Churn”
There are a million reasons to learn R (see e.g. Why R for Data Science – and not Python?), but where to start? I present to you the ultimate introduction to bring you up to speed! So read on…
Continue reading “Learning R: The Ultimate Introduction (incl. Machine Learning!)”
As promised in the post Learning Data Science: Modelling Basics we will now go a step further and try to predict income brackets with real world data and different modelling approaches. We will learn a thing or two along the way, e.g. about the so-called Accuracy-Interpretability Trade-Off, so read on…
Continue reading “Learning Data Science: Predicting Income Brackets”
One of the topics that is totally hyped at the moment is obviously Artificial Intelligence or AI for short. There are many self-proclaimed experts running around trying to sell you the stuff they have been doing all along under this new label.
When you ask them what AI means you will normally get some convoluted explanations (which is a good sign that they don’t get it themselves) and some “success stories”. The truth is that many of those talking heads don’t really know what they are talking about, yet happen to have a friend who knows somebody who picked up a book at the local station bookshop… ok, that was nasty but unfortunately often not too far away from the truth.
So, what is AI really? This post tries to give some guidance, so read on!
Continue reading “So, what is AI really?“
Everything “neural” is (again) the latest craze in machine learning and artificial intelligence. Now what is the magic of artificial neural networks (ANNs)?
Continue reading “Understanding the Magic of Neural Networks”
We already saw the power of the OneR package in the preceding post, One Rule (OneR) Machine Learning Classification in under One Minute. Here we want to give some more examples to gain some fascinating, often counter-intuitive, insights.
Continue reading “OneR – Fascinating Insights through Simple Rules”
Here I give a very short introduction on how to use the
OneR Machine Learning package for the hurried, so buckle up!
Continue reading “One Rule (OneR) Machine Learning Classification in under One Minute”