Put AI to work
June 26-27, 2017: Training
June 27-29, 2017: Tutorials & Conference
New York, NY
Josh Patterson

Josh Patterson
Director of Field Engineering, Skymind

Website

Josh Patterson is the director of field engineering for Skymind. Previously, Josh ran a big data consultancy, worked as a principal solutions architect at Cloudera, and was an engineer at the Tennessee Valley Authority, where he was responsible for bringing Hadoop into the smart grid during his involvement in the openPDC project. Josh is a cofounder of the DL4J open source deep learning project and is a coauthor on the upcoming O’Reilly title Deep Learning: A Practitioner’s Approach. Josh has over 15 years’ experience in software development and continues to contribute to projects such as DL4J, Canova, Apache Mahout, Metronome, IterativeReduce, openPDC, and JMotif. Josh holds a master’s degree in computer science from the University of Tennessee at Chattanooga, where he did research in mesh networks and social insect swarm algorithms.

Sessions

9:00am - 5:00pm Monday, June 26 & Tuesday, June 27
Location: Gibson
Secondary topics:  Deep Learning, Health care, IoT and its applications
Josh Patterson (Skymind), Susan Eraly (Skymind), Tom Hanlon (Functional Media)
Recurrent neural networks have proven to be very effective at analyzing time series or sequential data, so how can you apply these benefits to your use case? Josh Patterson, Tom Hanlon, and Susan Eraly demonstrate how to use Deeplearning4j to build recurrent neural networks for time series data. Read more.