The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.

Nishant Banjade

Last update: Sep 22, 2022

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Overview

Neural Machine Translation communication system

The model is basically direct to convert one source language to another targeted language using encoder and decoder architecture. The model encodes the message sent by the sender to a vector of fixed length and decoder generates the translated message which is received by the receiver in their communication system(chat application) automatically.

Prerequisites
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Prerequisites

Install python packages such as numpy pandas Tensorflow Django matplotlib

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About

The model is trained using the spanish-english dataset with 100 epochs. The dataset contains about 110k rows and took about 4 hours to train using Nvidia GTX 1650 graphics card.

Clone the project

git clone [email protected]:Nix-code/Nix-code-Neural-Machine-Translation-communication-system-.git

Basic knowledge of Django is must, as the Neural Machine Translation model is deployed on Django

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The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.

Related tags

Overview

Neural Machine Translation communication system

Table Of Contents

Prerequisites

Contribute

About

Clone the project

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