In this chapter, we first went deeper into the RNNs' main concepts, before understanding how many practical use cases these particular NNs have, and, finally, we started going hands-on, implementing some RNNs using DL4J and Spark.
The next chapter will focus on training techniques for CNN and RNN models. Training techniques have just been mentioned, or skipped from Chapter 3, Extract, Transform, Load, to this chapter because the main goal so far has been on understanding how training data can be retrieved and prepared and how models can be implemented through DL4J and Spark.
