In this chapter, we saw RNNs and how to use internal memory for their processing. We also covered CNNs, which are standardized neural networks mainly used for image recognition. For RNNs, we studied some sample implementations in R.
We learned how to train, test, and evaluate an RNN. We also learned how to visualize the RNN model in an R environment. We discovered the LSTM model. We introduced the concepts as CNN and a common CNN architecture: LeNet.
In the next chapter, we will see more use cases involving R implementations of neural networks and deep learning.