Neural Machine Translation (NMT) Project

This repository contains a Neural Machine Translation (NMT) project implemented in Python. The project includes a Jupyter Notebook (NMTranslation.ipynb) that demonstrates the end-to-end process of building a French-to-English translation model using sequence modeling techniques. The model includes Luong attention and scaled dot-product attention mechanisms.

Project Structure

The project is organized into separate Python files corresponding to the cell blocks in the original notebook. Each file focuses on a specific part of the translation pipeline, from data preprocessing to model training and evaluation.

Files

• data_preprocessing.py: Contains functions for loading and preprocessing the French-English sentence pairs.
• model_architecture.py: Defines the architecture of the translation model, including the encoder, decoder, and attention mechanisms.
• training.py: Includes the training loop and functions for training the NMT model.
• evaluation.py: Contains functions for evaluating the model's performance on the validation and test sets.
• utils.py: Utility functions used throughout the project.

Notebooks

• NMTranslation.ipynb: The original Jupyter Notebook demonstrating the complete process.

Getting Started

Prerequisites

• Python 3.10.7
• Jupyter Notebook
• Required Python packages (listed in requirements.txt)

Installation

1. Clone the repository:

   git clone https://github.com/SitanshuA091/Neural-Machine-Translation