Deeplearning4j on Spark and Data Science on the JVM with nd4j

Hosted by Bay Area Spark Meetup

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Update: we'll share the social hour with Galvanize Open House. Please join us at 6pm for the Galvanize take on data science education and how to make world-class data scientists for your startup.

DeepLearning4j (http://deeplearning4j.org/) is an open source deep learning platform for the JVM focusing on data at scale and ease of use and maintainability. In this talk we will be covering the core architecture of deeplearning4j on Spark. This will cover the 3 core components of deeplearning4j:

• A mini introduction to the scientific computing library nd4j (nd4j.org (http://nd4j.org/))

• The core algorithms in deeplearning4j

• Distributed Deep Learning, using Jeff Dean Style Parameter averaging

Each part of the talk will involve brief live coding to demonstrate concepts and takeaways. We will end with a runtime comparison of MLlib and deeplearning4j on Spark.

Adam Gibson is the co-founder of Skymind (http://skymind.io), an enterprise deep-learning and NLP firm, and creator of the distributed, open-source frameworks Deeplearning4j.org and ND4J.org. Adam has taught machine-learning at Zipfian Academy and is currently deep-learning specialist in residence at GalvanizeU (http://www.galvanizeu.com/) (our gracious hosts!). Adam has spoken at Hadoop Summit, OSCon and Tech Planet in Seoul, and is the author of the forthcoming O'Reilly book: "A Practitioner's Guide to Deeplearning4j." Adam consults for hedge funds, Fortune 500 companies and startups. He studied CS at Michigan Tech, and lives in Oakland.

Agenda:

6:00 Galvanize Open House and social hour

7:00 Deeplearning4j