Presented By O'Reilly and Cloudera
Make Data Work
December 1–3, 2015 • Singapore

Enterprise Deep Learning Workflows with DL4J

Josh Patterson (Skymind)
4:50pm–5:30pm Thursday, 12/03/2015
Data Science and Advanced Analytics
Location: 321-322 Level: Advanced
Average rating: ****.
(4.00, 4 ratings)
Slides:   1-PPTX 

Prerequisite Knowledge

understanding of basic concepts of machine learning

Description

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.

Photo of Josh Patterson

Josh Patterson

Skymind

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”