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Home Categories Pytorch

Pytorch Seq2Seq Tutorial for Machine Translation faq

instructor Instructor: Aladdin Persson instructor-icon
duration Duration: 1.00 duration-icon

This tutorial provides an overview of how to use Pytorch to create a sequence-to-sequence model for machine translation. It covers data processing using Torchtext, implementation of the encoder and decoder, putting it together to form a Seq2Seq model, setting up training, fixing errors, and evaluation. The tutorial provides a comprehensive guide to creating a machine translation model using Pytorch. ▼▲

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Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Free

providerProvider:

Youtube

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

On-Demand

Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [February 21st, 2023]

Unlock the Exciting World of Learning! Here's What Awaits You: With the Pytorch Seq2Seq Tutorial for Machine Translation, you can learn how to build a powerful machine translation system. You will learn how to import and process data using Torchtext, implement an encoder and decoder, and put it all together to create a Seq2Seq model. You will also learn how to set up training of the network, fix errors, and evaluate the model. Finally, you will learn how to calculate the Bleu score result to measure the accuracy of your model. With this tutorial, you can become an expert in machine translation and create powerful models that can be used in a variety of applications.

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Provider Youtube's Stats at AZClass

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