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 and data analysts who might have no math or data science background.
The chapter covers the following topics:
- Long short-term memory (LSTM...
