Welcome to the new issue of the Machine Learning Magazine! This time we will focus on a central trend in the current ML debate: As machine learning models inexorably enter our daily lives, the question of how decisions are made on the basis of these models is becoming increasingly urgent. How do we achieve explainability?
This issue of ML magazine is also peppered with a wealth of other topics. To start with, Daniel Costea gives us a detailed introduction to the Machine Learning Framework ML.NET, whereas Nicolas Kuhaupt demonstrates the real-time anomaly detection with Kafka and Isolation Forests. And finally, Jens Caasen answers the question about how machine learning and the Universal Windows Platform (UWP) can be brought together.
Register for the ML Conference newsletter to receive the second magazine issue: