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GRU cells are better than simpleRNN

In this exercise you will re-run the same model as the first chapter of the course to compare the accuracy of the model by simpling changing the SimpleRNN cell to a GRU cell.

The model was already trained with 10 epochs, as in the previous model with a SimpleRNN cell. In order to compare the models, a test set (x_test, y_test) is already loaded in the environment, as well as the old model SimpleRNN_model.

This exercise is part of the course

Recurrent Neural Networks (RNNs) for Language Modeling with Keras

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Exercise instructions

  • Import the GRU cell.
  • Print the models' summaries.
  • Print the accuracy of each model.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Import the modules
from tensorflow.keras.layers import ____, Dense

# Print the old and new model summaries
SimpleRNN_model.____
gru_model.____

# Evaluate the models' performance (ignore the loss value)
_, acc_simpleRNN = SimpleRNN_model.evaluate(X_test, y_test, verbose=0)
_, acc_GRU = gru_model.evaluate(X_test, y_test, verbose=0)

# Print the results
print("SimpleRNN model's accuracy:\t{0}".format(____))
print("GRU model's accuracy:\t{0}".format(____))
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