Data Science #9 - The Unreasonable Effectiveness of Mathematics in Natural Sciences, Eugene Wigner

In this special episode, Daniel Aronovich joins forces with the 632 nm podcast. In this timeless paper Wigner reflects on how mathematical concepts, often developed independently of any concern for the physical world, turn out to be remarkably effective in describing natural phenomena. This effectiveness is "unreasonable" because there is no clear reason why abstract mathematical constructs should align so well with the laws governing the universe. Full paper is at our website: https://datasciencedecodedpodcast.com/episode-9-the-unreasonable-effectiveness-of-mathematics-in-natural-sciences-eugene-wigner-1960

Om Podcasten

We discuss seminal mathematical papers (sometimes really old 😎 ) that have shaped and established the fields of machine learning and data science as we know them today. The goal of the podcast is to introduce you to the evolution of these fields from a mathematical and slightly philosophical perspective. We will discuss the contribution of these papers, not just from pure a math aspect but also how they influenced the discourse in the field, which areas were opened up as a result, and so on. Our podcast episodes are also available on our youtube: https://youtu.be/wThcXx_vXjQ?si=vnMfs