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How to Train and Test an AI Language Translation System

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19 Apr 2021CPOL3 min read 6.5K   100   2  
In this article, we’ll train and test the model we created in the previous entry in the series.
Here we'll create a Keras tokenizer that will build an internal vocabulary out of the words found in the parallel corpus, use a Jupyter notebook to train and test our model, and try running our model with self-attention enabled.

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This article is part of the series 'Using Deep Learning for Automatic Translation View All

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)


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