NMT is a type of machine translation that uses neural networks to learn the mapping between languages.
Unlike traditional machine translation, which uses statistical models and rule-based approaches, NMT uses a neural network architecture.
The neural network is trained on parallel texts, which are pairs of sentences in the source and target languages.
NMT models can be trained end-to-end, which means that the model learns to translate from the source language to the target language in a single step.
NMT models can handle multiple language pairs, and can be trained to translate between any two languages.
NMT is particularly effective for translating languages with complex syntax and morphology.
NMT models can be used for a wide range of applications, including document translation, website localization, and customer support.
NMT models can be deployed in the cloud, on-premises, or on mobile devices.