Python dominiert die Welt des Machine Learning weitgehend, aber im kommerziellen Bereich wird zumeist mit der Java Virtual Machine gearbeitet. In diesen Kontexten kann es nötig sein, TensorFlow-Modelle mit Java zu kombinieren. Christian Henkelmann verrät in diesem Video einige Tipps und Tricks, wie sich die JVM-Infrastruktur in diesen Fällen leichtern nutzen lässt und man ohne doppelten Code auskommt. Der Speaker zeigt in seiner Session von der ML Conference, wie man TensorFlow-Modelle auf die JVM bekommt und was dabei zu beachten ist.
Efficient Transformers
Christoph Henkelmann, DIVISIO
Enhancing Page Visits by Topic Prediction
Dieter Jordens, Continuum Consulting NV
Machine Learning on Edge using TensorFlow
Håkan Silfvernagel, Miles AS
Der Speaker: Christoph Henkelmann
Christoph Henkelmann holds a degree in Computer Science from the University of Bonn. He is currently working at DIVISIO, an AI company from Cologne, where he is CTO and co-founder. At DIVISIO, he combines practical knowledge from two decades of server and mobile development with proven AI and ML technology. In his pastime he grows cacti, practices the piano and plays video games.
Christoph Henkelmann holds a degree in Computer Science from the University of Bonn. He is currently working at DIVISIO, an AI company from Cologne, where he is CTO and co-founder. At DIVISIO, he combines practical knowledge from two decades of server and mobile development with proven AI and ML technology. In his pastime he grows cacti, practices the piano and plays video games.
