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## 6.6. Interpreting the RNN 

One of the main criticisms of neural networks is the fact that no explicit, human understandable model is created; the learning consists entirely in the optimization of the values of thousands or millions of floating point parameters. We present two ways in which users can gain insight into what the neural net has learned, i.e. the knowledge that is encoded in its structures. 

