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Romeo Kienzler

Chief Data Scientist at IBM Watson IoT

Romeo Kienzler holds a M. Sc. (ETH) in  Information Systems, Bioinformatics & Applied Statistics (Swiss Federal Institute of Technology). He has nearly two decades of experience in Software Enineering, Database Administration and Information Integration. Since 2012 he works as a Data Scientist for IBM. He published several works in the field with international publishers and on conferences. His current research focus is on massive parallel data processing architectures. Romeo also contributes to various open source projects.Romeo Kienzler works as Associate Professor for Data Mining and is a member of the IBM Academy of Technology.

Realtime – Cognitive IoT using DeepLearning and Online Learning on top of ApacheSpark Streaming and Spark enabled DL frameworks

Apr 20, 2017

DeepLearning frameworks are popping up at very high frequency but only a few of them are suitable to run on clusters, use GPUs and supporting topologies beyond Feed-Forward at the same time. DeepLearning4J features all this without forcing you to learn new exotic programming languages and in addition also scales-out on well-established infrastructures like ApacheSpark and Hadoop/YARN. In this keynote, we will introduce DeepLearning4J on top of ApacheSpark with an example to create an anomaly detector for IoT sensor data with a LSTM auto encoder neural network.