Summary
Text augmentation with machine learning (ML) is an advanced technique. We used a pre-trained ML model to create additional training NLP data.
After inputting the first three paragraphs, the T5 NLP ML engine wrote the preceding summary for this chapter. It is perfect and illustrates the spirit of this chapter. Thus, Pluto has kept it as-is.
In addition, we discussed 14 NLP ML models and four word augmentation methods. They were Word2Vec, BERT, RoBERTa, and back translation.
Pluto demonstrated that BERT and RoBERTa are as good as human writers. The augmented text is not just merely appropriate but inspirational, such as replacing it was the age of foolishness with death was the age of love or it was the epoch of belief with it was the age of youth.
For the back translation method, Pluto used the Facebook or Meta AI NLP model to translate to German and Russian and back to English.
For sentence augmentation, Pluto dazzled with the accuracy of the T5 NLP ML engine...
