aflah02/Easy-Data-Augmentation-Implementation

My Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks using Tensorflow

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This tool helps improve the accuracy of models that categorize text, like sentiment analyzers. You provide your existing text classification data, and it generates expanded versions of that data with subtle variations. This is ideal for machine learning practitioners or data scientists who work with text and need to train more robust classification models, especially with limited initial data.

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Use this if you have a text classification problem and want to boost your model's performance without needing a lot of additional original data.

Not ideal if you are not working with text classification or if you already have an abundance of training data and are not seeing performance plateaus.

text-classification natural-language-processing machine-learning-engineering data-science
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Last pushed

Mar 18, 2022

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