Pytorch Seq2Seq Tutorial for Machine Translation
Learners:
Instructor: Aladdin Persson
Duration: 1.00
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.▼
Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
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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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