One major force behind the latest developments in artificial intelligence is machine learning. Machine learning deals with algorithms that improve through experience over time. There are different ways a machine can learn. Reinforcement learning is one of them. With reinforcement learning, the computer learns to master a task by interacting with its environment through reward and punishment, trying to maximize its reward. This post uses a mini-chess game called hexapawn to explore how a computer can learn through reinforcement learning.

Play the game on https://www.stefanseegerer.de/schlag-das-krokodil/?robots=true

The game

Hexapawn (or mini chess) originates from an idea by Martin Gardner, who used it to explain machine learning as early…


Supervised learning is about learning a mapping between input and output data. A common application is classification tasks, where the class for a given data point is to be predicted.

In the training phase, a supervised learning algorithm learns a pattern by which the correct labels (e.g. classes) can be assigned to the data based on known examples. This is stored in a model.

To assess the quality of the model, additional data is used (test data). The predicted classes are compared with the actual classes. …


Beim überwachten Lernen geht es darum, eine Zuordnung zwischen Ein- und Ausgabedaten zu lernen. Eine häufige Anwendung stellen sogenannte Klassifikationsaufgaben dar, bei denen die Klassenzugehörigkeit für einen gegebenen Datenpunkt vorhergesagt werden soll.

In der Trainingsphase lernt ein überwachtes Lernverfahren auf Basis bekannter Beispiele eine Zuordnung von Eingabe zu Ausgabe. Diese wird in einem Modell gespeichert.

Um die Güte des Modells bestimmen zu können, werden nun weitere Daten herangezogen. Dazu wird das Modell auf die Testdaten angewendet und die vom Modell vorhergesagten mit den eigentlichen Klassenzugehörigkeiten verglichen. Dafür stehen uns verschiedene sogenannte Metriken zur Verfügung, wobei unterschiedliche Anwendungsfälle unterschiedliche Metriken erfordern.


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 influence of AI on our society. Therefore, we do not consider any technical details or provide an introduction on how to use certain machine learning frameworks. Instead, we focus on explaining the underlying ideas of machine learning which empower everyone to understand and shape the digital world that surrounds us.

Machine learning is becoming increasingly important in more and more areas of life and achieves remarkable results. This is even more impressive given the fact…


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 influence of AI on our society. Therefore, we do not consider any technical details or provide an introduction on how to use certain machine learning frameworks. Instead, we focus on explaining the underlying ideas of machine learning which empower everyone to understand and shape the digital world that surrounds us.

“Ouch, that’s hot!” — After their first encounter with a hot plate, children quickly learn not to touch it… That’s because children learn through direct…


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 influence of AI on our society. Therefore, we do not consider any technical details or provide an introduction on how to use certain machine learning frameworks. Instead, we focus on explaining the underlying ideas of machine learning which empower everyone to understand and shape the digital world that surrounds us.

If we take a large pile of Lego bricks and ask three children to sort them, the children will most probably create several smaller piles…


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 influence of AI on our society. Therefore, we do not consider any technical details or provide an introduction on how to use certain machine learning frameworks. Instead, we focus on explaining the underlying ideas of machine learning which empower everyone to understand and shape the digital world that surrounds us.

For many children, a dog is the animal they ever encounter (“a bow-wow”). Initially, a child will apply this term to other animals as well…


An Introduction of the underlying Ideas in Machine Learning

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 influence of AI on our society. Therefore, we do not consider any technical details or provide an introduction on how to use certain machine learning frameworks. Instead, we focus on explaining the underlying ideas of machine learning which empower everyone to understand and shape the digital world that surrounds us.

How can cars “learn” to drive autonomously? How do computers recognize cancer cells? And does my online shop know what I want to buy? Recent…

Stefan Seegerer

Researcher | Developer | Speaker | Educator

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store