This is my own learning plan for getting similar knowledge to that of an MBA, without the high cost of actually getting a degree.
Transferring personal data to USA from EU is currently problematic under the GDPR. This post summarises the situation at the moment.
There is a lot of confusion in the news and elsewhere about what food is healthy for us, but beyond the noise, public confusion, and fad diets there exists solid science by now. This post looks at what is actually healthy!
Since my old computer was getting very old, I decided that it was finally time to build a new computer and allocate a generous budget this time.
Explains what order statistics, selection algorithms, and percentiles are and various ways of computing them. Also benchmarks in Python and Rust.
Implementation guide for calculating nonparametric confidence intervals of the population mean based on the Dvoretzky–Kiefer–Wolfowitz inequality.
During 2021, I read 68 books. I give some highlights from my year in books here by presenting 20 favourites in a few different categories.
Nassim Taleb’s “The Black Swan: The Impact of the Highly Improbable” is a long but great description of the common pitfalls when reasoning about risks and probabilities in the real world. A must-read for all data scientists, statisticians, and decision makers.
Walter Rudin’s classic book, often called “baby Rudin”, is one of the most famous mathematics books. The third and final edition was published in 1976 and it remains both loved and hated by many mathematicians.
What are floating-point numbers? When is it a bad idea to compare them? How precise are they? Let’s explore this.