Machine Translation with Keras

In this chapter, you'll understand what the encoder-decoder architecture is and how it is used for machine translation. You will also learn about Gated Recurrent Units (GRUs) and how they are used in the encoder-decoder architecture.

In this chapter, you will implement the encoder-decoder model with the Keras functional API. While doing so, you will learn several useful Keras layers such as RepeatVector and TimeDistributed layers.

In this chapter, you will train the previously defined model and then use a well-trained model to generate translations. You will see that our model does a good job when translating sentences.

In this chapter, you will learn about a technique known as Teacher Forcing, which enables translation models to be trained better and faster. Then you will learn how you can use word embeddings to make the model even better.