In this project I am applying the knowledge learned about RNN to test different architectures to develop a translator model. The first architecture tested is a bidirectional RNN and the second is an Encoder-Decoder. The technical explanation to the architects and the training process are explained in the Notebook.
The Dataset used in this project was created by Udacity to be used in the NLP Nanodegree. To create the code we used python, and the Pytorch library, CUDA was used to train the model.