How Things Work – Page 2 – Learning Machines

How to Catch a Thief: Unmasking Madoff’s Ponzi Scheme with Benford’s Law

One of my starting points into quantitative finance was Bernie Madoff’s fund. Back then because Bernie was in desperate need of money to keep his Ponzi scheme running there existed several so-called feeder funds.

One of them happened to approach me to offer me a once-in-a-lifetime investment opportunity. Or so it seemed. Now, there is this old saying that when something seems too good to be true it probably is. If you want to learn what Benford’s law is and how to apply it to uncover fraud, read on!
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“You Are Here”: Understanding How GPS Works

Last week, I showed you a method of how to find the fastest path from A to B: Finding the Shortest Path with Dijkstra’s Algorithm. To make use of that, we need a method to determine our position at any point in time.

For that matter, many devices use the so-called Global Positioning System (GPS). If you want to understand how it works and do some simple calculations in R, read on!
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Finding the Shortest Path with Dijkstra’s Algorithm

I have to make a confession: when it comes to my sense of orientation I am a total failure… sometimes it feels like GPS and Google maps were actually invented for me!

Well, nowadays anybody uses those practical little helpers. But how do they actually manage to find the shortest path from A to B?

If you want to understand the father of all routing algorithms, Dijkstra’s algorithm, and want to know how to program it in R read on!
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Local Differential Privacy: Getting Honest Answers on Embarrassing Questions

Do you cheat on your partner? Do you take drugs? Are you gay? Are you an atheist? Did you have an abortion? Will you vote for the right-wing candidate? Not all people feel comfortable answering those kinds of questions in every situation honestly.

So, is there a method to find the respective proportion of people without putting them on the spot? Actually, there is! If you want to learn about randomized response (and how to create flowcharts in R along the way) read on!
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Kalman Filter as a Form of Bayesian Updating

The Kalman filter is a very powerful algorithm to optimally include uncertain information from a dynamically changing system to come up with the best educated guess about the current state of the system. Applications include (car) navigation and stock forecasting. If you want to understand how a Kalman filter works and build a toy example in R, read on!
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Learning Data Science: A/B Testing in Under One Minute

Google does it! Facebook does it! Amazon does it for sure!

Especially in the areas of web design and online advertising, everybody is talking about A/B testing. If you quickly want to understand what it is and how you can do it with R, read on!
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Will AI become conscious any time soon?

We all know the classical Sci-Fi trope of intelligent machines becoming conscious and all the potential ramifications that could follow from there (free will, fighting their human creators, ethical dilemmas, and so forth). Now, is this a realistic scenario? As a researcher in the area of AI (see e.g. So, what is AI really?), with a penchant for philosophy, I share my thoughts here with you, so read on!
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COVID-19 in the US: Back-of-the-Envelope Calculation of Actual Infections and Future Deaths

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 the US, read on!
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Collider Bias, or Are Hot Babes Dim and Eggheads Ugly?

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 want to learn about a paradoxical effect nearly nobody is aware of, where correlation between two uncorrelated random variables is introduced just by sampling, read on!
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COVID-19: The Case of Germany

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?! Indeed, if you want to find out what the numbers tell us how things might develop here, read on!
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