Summary

In this chapter, we talked in detail about NMT systems. Machine translation is the task of translating a given text corpus from a source language to a target language. First, we talked about the history of machine translation briefly to build a sense of appreciation for what has gone into machine translation for it to become what it is today. We saw that today, the highest-performing machine translation systems are actually NMT systems. Next, we solved the NMT task of generating English to German translations. We talked about the dataset preprocessing that needs to be done, and extracting important statistics about the data (e.g. sequence lengths). We then talked about the fundamental concept of these systems and decomposed the model into the embedding layer, the encoder, the context vector, and the decoder. We also introduced techniques like teacher forcing and Bahdanau attention, which are aimed at improving model performance. Then we discussed how training and inference...