Get the free Ebook:
Private and Open Data in Asia: A Regional Guide.
As the data world undergoes its cambrian explosion phase our data tools need to become more advanced to keep pace. Deep Learning has emerged as a key tool in the non-linear arms race of machine learning. Applications in text, sensor processing (IoT), image processing, and audio processing have all emerged as prime deep learning applications. In this session we will take a look at a practical review of what is deep learning and introduce DL4J. We’ll look at how it supports deep learning in the enterprise on the JVM. We’ll discuss the architecture of DL4J’s scale-out parallelization on Hadoop and Spark in support of modern machine learning workflows. We’ll conclude with a workflow example from the command line interface that shows the vectorization pipeline in Canova producing vectors for DL4J’s command line interface to build deep learning models easily.
Josh Patterson currently runs a consultancy in the Big Data Machine Learning space and is an advisor to Skymind (deep learning startup). 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. Josh is a graduate of the University of Tennessee at Chattanooga with a Masters of Computer Science where he did research 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. Josh is the co-author of the upcoming Oreilly book titled “Deep Learning: A Practitioner’s Approach”
©2015, O'Reilly Media, Inc. • (800) 889-8969 or (707) 827-7019 • Monday-Friday 7:30am-5pm PT • All trademarks and registered trademarks appearing on oreilly.com are the property of their respective owners. • firstname.lastname@example.org
Apache Hadoop, Hadoop, Apache Spark, Spark, and Apache are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries, and are used with permission. The Apache Software Foundation has no affiliation with and does not endorse, or review the materials provided at this event, which is managed by O'Reilly Media and/or Cloudera.