Neural Machine Translation (NMT) is a type of machine translation that uses an artificial neural network to predict the likelihood of a sequence of words. It is a deep learning approach that has been shown to be effective in improving the quality of machine translation.
In NMT, the neural network is trained on a large corpus of parallel sentences in two languages. The network learns to map the input sentence in one language to the output sentence in another language. The neural network consists of an encoder and a decoder. The encoder takes the input sentence and converts it into a fixed-length vector representation. The decoder then takes this vector representation and generates the output sentence word by word.