Articles by Learning Machines

Kalman Filter as a Form of Bayesian Updating

July 7, 2020 | Learning Machines

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 ... [Read more...]

COVID-19: False Positive Alarm

June 23, 2020 | Learning Machines

In this post, we are going to replicate an analysis from the current issue of Scientific American about a common mathematical pitfall of Coronavirus antibody tests with R. Many people think that when they get a positive result of such a test they are immune to the virus with high ... [Read more...]

Thomas Ramge: Postdigital (Book Excerpt)

June 16, 2020 | Learning Machines

We are honoured to present to you an exclusive excerpt from digital thought leader and bestselling author Thomas Ramge’s new book Postdigital. Using AI to Fight Coronavirus, Foster Wealth and Fuel Democracy: In concrete terms, what would a postdigital world look like in which people — both individually and as ... [Read more...]

Learning R: Build a Password Generator

June 2, 2020 | Learning Machines

It is not easy to create secure passwords. The best way is to let a computer do it by randomly combining lower- and upper-case letters, digits and other printable characters. If you want to learn how to write a small function to achieve that read on! The exact task is ... [Read more...]

Learning Statistics: Randomness is a Strange Beast

May 26, 2020 | Learning Machines

Our intuition concerning randomness is, strangely enough, quite limited. While we expect it to behave in certain ways (which it doesn’t) it shows some regularities that have unexpected consequences. In a series of seemingly random posts, I will highlight some of those regularities as well as consequences. If you ... [Read more...]

Will AI become conscious any time soon?

May 12, 2020 | Learning Machines

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. ... [Read more...]

COVID-19: Analyze Mobility Trends with R

April 21, 2020 | Learning Machines

The global lockdown has slowed down mobility considerably. This can be seen in the data produced by our ubiquitous mobile phones. Apple is kind enough to make those anonymized and aggregated data available to the public. If you want to learn how to get a handle on those data and ... [Read more...]

Collider Bias, or: Are Hot Babes Dim and Eggheads Ugly?

March 24, 2020 | Learning Machines

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...]

COVID-19: The Case of Germany

March 17, 2020 | Learning Machines

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...]
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