Pytorch Transformers for Machine Translation
Learners:
Instructor: Aladdin Persson
Duration: 1.00
This course provides an introduction to using Pytorch Transformers for Machine Translation. It covers data preprocessing, setting up a Transformer network, training the model, fixing errors, and evaluating the model with a BLEU score. It provides a comprehensive overview of the process for those interested in using Pytorch Transformers for Machine Translation.▼
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]
This course provides a comprehensive introduction to the Pytorch Transformer library for machine translation. Learners will learn how to use the library to preprocess data, set up a transformer network, and evaluate the model. They will also learn how to fix errors and calculate the BLEU score.
include:
- Applying the Pytorch Transformer library to other natural language processing tasks such as text summarization, question answering, and sentiment analysis.
- Developing more advanced transformer networks for machine translation.
- Exploring other libraries and frameworks for machine translation.
Learning Suggestions for learners include:
- Learning more about natural language processing and machine translation.
- Exploring other libraries and frameworks for machine translation.
- Practicing with different datasets and tasks.
- Developing a deeper understanding of the transformer architecture.
- Learning more about the BLEU score and other evaluation metrics.
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