The idea behind the model-agnostic technique LIME is to approximate a complex model locally by an interpretable model and to use that simple model to explain a prediction of a particular instance of interest.

This is the second part of our series about Machine Learning interpretability. We want to describe LIME (Local Interpretable Model-Agnostic Explanations), a popular t

This blog explains the basic concept of Reinforcement Learning, giving you an understanding of the closed loop system, in which an agent uses actions to change the state of the environment and thus receives rewards, with the goal of maximizing the return.

I would like to start this series about reinforcement learning by giving an overview of what reinforcement learning is, what it is used for and what terminology is ne

Entropy is a significant, widely used and above all successful measure for quantifying eg. inhomogeneity, uncertainty or unpredictability. It is an integral part of the latest machine learning models deployed on real-world data sets. In this article, I want to highlight the simplicity, beauty and meaning of entropy.

If you are dealing with Statistics, Data Science, Machine Learning, Artificial Intelligence or even general Computer Science, Mathematics, Engineering or Physics, you

Everybody talks about AI and deep learning and everybody uses it, including you! But what exactly is deep learning and what are artificial neural networks? In this article I shine a light on some basic yet crucial concepts in an attempt to lift the veil.

Artificial intelligence or deep learning: Everybody talks about it and everybody uses it, including you! Of course you immediately have the evil terminator in mind wh

I use state-of-the-art NLP techniques to improve an existing pricing model in an online car market. Online car markets usually use technical car attributes for price prediction with sellers adding description texts to provide more details. In my thesis, I use these texts to improve the existing pricing model.

tl;dr: This blog post summarizes my masters‘ thesis. I use state-of-the-art NLP techniques to improve an existing pricing model in an online car market. Online

This article presents SeqPolicyNet, our Deep Learning approach to accessing information stored in an Elasticsearch instance given natural language questions.

tl;dr (spoiler alert): We’ve trained an advanced neural network to query Elasticsearch based on natural language questions. Our model, called SeqPolicyNet, incorporat

This article unveils the connections between artificial intelligence, machine learning and deep learning based on a simple example. It suits as an introduction for newbies as well as a reference point for advanced readers looking for more complex content.

There has always been a gap between the capabilities of men and machine. While computers were able to perform complex multiplications or store large amounts of data,