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 talk presented at the PyCon 2013 in Cologne gives a small introduction of how Blue Yonder applies machine learning and Predictive Analytics in various fields as well as the challenges of Big Data. Using the example of Blue Yonder’s machine learning software NeuroBayes, I show the made efforts …