Text Classification with the Naive Bayes Text Classifier
The Naive Bayes classifier is a simple and efficient algorithm for classification tasks that assumes independence of the features. This post aims to introduce this algorithm to the reader.
Dimensionality Reduction with Random Projections
Large amounts of data can be challenging for many reasons. Today, I will present an algorithm that can be used to reduce the size of a data set: Random Projections.
Unlocking the Power of T5: The Versatile Language Model for Text-to-Text Tasks
T5 is a powerful language model capable of performing a wide range of text-to-text tasks, including text classification, language translation or text summarization. The aim of this post is to introduce this pretrained transformer to the reader.
Ethics and Bias in Machine Learning
As in many other areas, ethical issues are necessary for the safe and fair use of various products. In this article, we will look at ethical issues related to machine learning.
Robust clustering using k-Means
To identify similar groups in unknown data and reduce complexity, clustering can be used. Here we describe the k-means algorithm that can be used for clustering.
"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.
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.
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.