January 2019
Intermediate to advanced
322 pages
7h 29m
English
Content preview from Hands-On Deep Learning with Apache Spark
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Recurrent Neural Networks
In this chapter, we are going to learn more about Recurrent Neural Networks (RNNs), an overview of their most common use cases, and, finally, a possible implementation by starting to be hands-on using the DeepLearning4j framework. This chapter's code examples involve Apache Spark too. As stated in the previous chapter for CNNs, training and evaluation strategies for RNNs will be covered in Chapter 7, Training Neural Networks with Spark, Chapter 8, Monitoring and Debugging Neural Network Training, and Chapter 9, Interpreting Neural Network Output.
In this chapter, I have tried to reduce the usage of math concepts and formulas as much as possible in order to make the reading and comprehension easier for developers ...
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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.