On-Policy and Off-Policy: What is 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.
Colophon: How we build Aggregata
Today we'll give you an inside look at the design and technical implementation decisions behind Aggregata.
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.
Introduction to Reinforcement Learning
This post is intended to introduce the reader to the basic topic of reinforcement learning. The introduction clarifies important terms and basic concepts that are used in Reinforcement Learning.
Generative texts: Working with Artificial Intelligence
How can you use artificial intelligence to generate creative and valuable texts? In this post, you'll learn more about the opportunities and challenges of generative texts.
Introduction to Semi Supervised Learning
Semi supervised learning represents one of the four topics of machine learning. This post is intended to give an introduction to the topic.
The Search Function - Redefined by Machine Learning
Microsoft and OpenAI, based on the immense success of ChatGPT, present a new way to search the Internet for information, starting a competition for Google's domination of the Internet.
Introduction to Unsupervised Learning
Unsupervised Learning represents one of the four topics of Machine Learning. This post aims to provide an introduction to the topic.
Introduction to Supervised Learning
Supervised Learning represents one of the four topics of Machine Learning. This post is intended to provide an introduction to the topic.
Artificial Neural Networks - A Milestone in Machine Learning
Neural networks are a hotly debated topic. But what are they and how exactly do they work? Some of these questions are answered here.
Machine Learning - Sounds interesting, but whats the matter?
Machine Learning is taking an increasingly important part in our lives. This post will explain why is likely a relevant concept in the future.
Visualize and update products with Alpine.js
In this post, we'll show you how to use Alpine.js to visualize a list of products and automatically convert their prices.
Double Deep Q-Network: DQN with stability upgrades
The Deep Q network sometimes suffers from various problems. The problems are presented here and a solution for these problems is presented.
Interactive forms with Alpine.js
In this post, I dynamize a contact form using Alpine.js to incrementally enrich the user experience.
Deep Recurrent Q Network - DQN with a look into the past
Deep Q-Networks sometimes need information from different time steps to converge quickly. The Deep Recurrent Q-Network represents one possibility for this.
Hyperparameter optimization for neural networks
How exactly does one perform hyperparameter optimization? What do you have to pay attention to there? What exactly does a visualization look like? There is an answer to all these questions here.
Deep Q Network - Deep Learning and Reinforcement Learning in a simple way
Artificial neural networks have achieved success in many fields. Here I present the first algorithm for training neural networks for reinforcement learning: the Deep Q-Network.
Linear Regression: Identifying Simple Correlations in Data
In the Big Data business, (co-)rellations are often useful to make decisions. Here is one easy method to find such information: Linear Regression.
Include Alpine.js in a production environment
To increase the interactivity of a production-ready PHP environment, I implemented Alpine.js for the first time. Here are my findings.