Text Augmentation To Boost NLP Model Performance (Part 1/3)

The more data we have, the better model performance we may achieve. However, it is often too costly and time-consuming to annotate a large amount of training data. Therefore, proper data augmentation is useful to boost up your model performance. The nlpaug module implements a number of high-performance text augmentation algorithms that may significantly boost performance of NLP models. This tutorial introduces some cool text augmentation functions in the nlpaug module. Topics include:
What is text augmentation and why is it useful for natural language processing tasks?
What are some of the examples of text augmentation?
How to install and import the dependences for running the nlpaug module successfully?
How to download required models to be used by the nlpaug module?
What are the four common options to create word level text augmentation using the nlpaug module?
What are the pros and cons of using different ways and models for text augmentation?
How can I choose between different options and models for text augmentation?
What is back translation?
How can I use Hugging Face base models (Bert, Roberta, etc.) in text augmentation?
How can I use synonyms in text augmentation?
How can I use fasttext, word2vec, and glove models in text augmentation?
Code used in this video can be downloaded from GitHub:
github.com/DreamJarsAI/Apply-...
Hashtags: #nlp #naturallanguageprocessing #text #augmentation #ai #nlptraining #nlppractitioner #artificialintelligence #machinelearning #deeplearning #python #pythonprogramming #pythontutorial #aitutorial #coding

[@caiyu538]

NLP data augmentation is more difficult than image data augmentation. Great lectures.

[@omarbadr9469]

I really want to thank you for this great series. I have been struggling to find a good resource on text augmentation and text imbalance. Until I found your channel. Thank you for this amazing series.

[@applyailikeapro7191]

You're very welcome!

[@caiyu538]

Great lectures. I plan to use this strategy to augment my data.

[@picassoofai4061]

subscribed and hit the like button in the first 5 seconds, Great channel and Great Content.