Machine translation

This project is a machine translation system developed using Natural Language Processing (NLP) techniques. It focuses on translating text from one language to another, leveraging modern deep learning architectures such as the Transformer model. The system is trained on parallel corpora using a sequence-to-sequence model, where the encoder processes the source language and the decoder generates the translation in the target language.

The implementation includes preprocessing pipelines such as tokenization, padding, and attention mechanisms to enhance translation accuracy. The project is built using Python and libraries such as TensorFlow/Keras or PyTorch, and evaluated using metrics like BLEU score for translation quality.

Potential use cases include multilingual chatbots, real-time translation services, and aiding communication in cross-cultural environments.