January 2019
Intermediate to advanced
322 pages
7h 29m
English
Content preview from Hands-On Deep Learning with Apache Spark
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The DeepLearning4j framework
Before jumping into the first example, let's quickly introduce the DeepLearning4j (https://deeplearning4j.org/) framework. It is an open source (released under the Apache license 2.0 (https://www.apache.org/licenses/LICENSE-2.0)), distributed deep learning framework written for the JVM. Being integrated since its earliest releases with Hadoop and Spark, it takes advantage of such distributed computing frameworks to speed up network training. It is written in Java, so is compatible with any other JVM language (including Scala of course), while the underlying computations are written in lower level languages, such as C, C++, and CUDA. The DL4J API gives flexibility when composing deep neural networks. So it is possible ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.