Topic: Parallel Iterative Machine Learning on Hadoop and YARN
Speaker: Josh Patterson
Josh currently runs a consultancy in the Big Data Machine Learning space. Previously Josh worked as a Principal Solutions Architect at Cloudera and an engineer at the Tennessee Valley Authority where he was responsible for bringing Hadoop into the smartgrid during his involvement in the openPDC project. His focus in the smartgrid realm with Hadoop and HBase was using machine learning to discover and index anomalies in time series data. Josh is a graduate of the University of Tennessee at Chattanooga with a Bachelors in Business Management and a Masters of Computer Science with a thesis titled "TinyTermite: A Secure Routing Algorithm" where he worked in mesh networks and social insect swarm algorithms. Josh has over 15 years in software development and continues to contribute to projects such as Apache Mahout, Metronome, IterativeReduce, openPDC, and JMotif in the open source community. Currently Josh focuses on open source parallel linear modeling and optimization techniques.