One year of Aggregata: A review and outlook
In October 2022 we published our first article and in October 2023 we will not only review one year of Aggregata but also give an outlook on future projects.
"How does A.I. learn?" - Impressions from our first seminar
Understanding Artificial Intelligence - In our latest article we give an insight into our first seminar and our experienc
On-Policy vs Off-Policy: What's the Difference?
The purpose of this article is to introduce the reader to the basic topic of reinforcement learning. The introduction concretizes important terms and basic concepts used there.
Regression using neural networks
There are a number of ways to solve a regression task. In this article we will describe how such a regression task can be solved using a neural network.
Classification using neural networks
There are several classical algorithms to perform a classification. Here I describe an implementation using neural networks and my experiences with it.
Q-Learning: The Basics of Reinforcement Learning
Q-Learning was one of the first practical reinforcement learning algorithms. This post introduces this algorithm.
Temporary and persistent state management with Alpine.js
In this article, you'll learn how to use Alpine.js to manage both temporary and persistent states, and how to use it to optimize your user experience.
Random Forests - An upgrade for Decision Trees
Decision trees alone are often not sufficient to perform a meaningful classification. Random forests represent an improvement of the decision trees. I am going to present this method in the following post.
Classification via k-nearest-neighbor classifier
Classification can be done in many different ways and with many different algorithms. Today I will introduce the K-Nearest-Neighbour classifier.
Decision Trees - Graphical Explainable AI
Often machine learning models are complex and difficult to understand. This article describes a method that visualizes clear structures and decision criteria: Decision Trees.
Logistic Regression - Prediction of Event Occurrences
Event occurrence probabilities are often a complex problem to model. In this article, a basic method for this is presented: Logistic Regression.
Working with Artificial Intelligence: Risks & Side Effects
Artificial intelligence is a capable technology with great advantages. However, it is also associated with risks and side effects. In this article you will learn what you need to be aware of when working with artificial intelligence.