Reinforcing learning through Python Notebook
Pluto uses the Python Notebook to reinforce our understanding of text augmentation. He uses the batch function to display text in batches. This works similarly to the batch functions for images. In other words, it randomly selects new records and transforms them using the augmentation methods.
Pluto recommends running the batch functions repeatedly to gain a deeper insight into the text augmentation methods. There are thousands of text records in the Twitter and Amazon datasets. Each time you run the batch functions, it displays different records from the dataset.
As with the image augmentation implementation, the wrapper functions use the Nlpaug library under the hood. The wrapper function allows you to focus on the text transformation concepts and not be distracted by the library implementation. You can use another text augmentation library, and the wrapper function input and output will remain the same.