Stefan SeegererBeat the robots — Learning about machine learning with hexapawnMay 10, 2021May 10, 2021
Stefan SeegererSupervised Learning — When is a model “good enough”?Supervised learning is about learning a mapping between input and output data. A common application is classification tasks, where the…Apr 23, 2021Apr 23, 2021
Stefan SeegererÜberwachtes Lernen — Wann ist ein Modell “gut genug”?Beim überwachten Lernen geht es darum, eine Zuordnung zwischen Ein- und Ausgabedaten zu lernen. Eine häufige Anwendung stellen sogenannte…Apr 22, 2021Apr 22, 2021
Stefan SeegererThis is How Machines Learn! Machine Learning and Society (Part 5)Our goal with this series is to enable everyone to understand AI phenomena in their daily lives, as well as to actively shape the growing…Dec 9, 2020Dec 9, 2020
Stefan SeegererThis Is How Machines Learn! Reinforcement Learning (Part 4)Our goal with this series is to enable everyone to understand AI phenomena in their daily lives, as well as to actively shape the growing…Nov 20, 2020Nov 20, 2020
Stefan SeegererThis is how machines learn! Unsupervised Learning (Part 3)In this part of the series, we explore unsupervised learning — one of the ways machines can learn.Nov 11, 2020Nov 11, 2020
Stefan SeegererThis Is How Machines Learn Supervised Learning (Part 2)How can machines learn through supervised learning? A visual introduction.Oct 30, 2020Oct 30, 2020
Stefan SeegererThis is how Machines Learn! An Introduction of the underlying Ideas in Machine Learning (Part 1)How can cars “learn” to drive autonomously? How do computers recognize cancer cells? And does my online shop know what I want to buy?Oct 30, 2020Oct 30, 2020