Jakob Karalus

codecentric, Germany

Jakob is a IT-Consultant at codecentric focussing on DevOps and Data Science. His main interest is to play with exciting and evolving technologies around orchestration, automation and Machine Learning. Currently he helps a large Enterprise as a cluster operator at running a multi tenant kubernetes cluster.

Topic: Distributed Deep Learning with TensorFlow and Kubernetes

Training (Deep) Neural Networks can quickly become a very time consuming task. Training a single network can easily take hours/days. Even with ever increasing CPU/GPU speed, using a single machine becomes cumbersome. Fortunately distributed training is a feature of TensorFlow which can drastically speed up training.