With the advent of Deep Learning (DL), the field of AI made a giant leap forward and it is nowadays applied in many industrial use-cases. Especially critical systems like autonomous driving, require that DL methods not only produce a prediction but also state the certainty about the prediction in order …

Even in the age of big data labelled data is a scarce resource in many machine learning use cases. We evaluate generative adversarial networks (GANs) at the task of extracting information from vehicle registrations under a varying amount of labelled data and compare the performance with supervised learning techniques. Using unlabelled data shows a significant improvement.

At mobile.de, Germany’s biggest car marketplace, a dedicated team of data engineers and scientists, supported by the IT project house inovex is responsible for creating intelligent data products. Driven by our company slogan “Find the car that fits your life”, we focus on personalised recommendations to address several …

In the field of machine learning and particularly in supervised learning, correlation is crucial to predict the target variable with the help of the feature variables. Rarely do we think about causation and the actual effect of a single feature variable or covariate on the target or response. Some even …

This talk presented at the PyData Amsterdam 2016 explains the idea of Bayesian model selection techniques, especially the Automatic Relevance Determination. The slides of this talk are available on SlideShare.

Even in the era of Big Data there are many real-world problems where the number of input features has about …

Scikit-Learn is a well-known and popular framework for machine learning that is used by Data Scientists all over the world. In this tutorial presented at the EuroPython 2014 in Berlin, I show in a practical way how you can add your own estimator following the interfaces of Scikit-Learn. First a …

The german Modellansatz podcast curated by Gudrun Thäter and Sebastian Ritterbusch, supported by the Karlsruhe Institute for Technology (KIT), conveys the importance of mathematics and mathematical modeling in our everyday life. Starting from the water tap, automatic velocity control systems on highways to your mobile phone, mathematics is almost everywhere …