protonx-tf-03-projects/CharCNN
Implementation of paper: Character-level Convolutional Networks for Text Classification
This project helps data science practitioners classify English sentences. You provide a CSV file with sentences and their corresponding labels (like positive/negative sentiment), and it processes this to build a classification model. The output is a trained model that can then take new sentences and predict their labels, delivered in a new CSV file. This is for data scientists or NLP engineers who need to categorize text.
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Use this if you need to classify English sentences based on their content, like categorizing customer feedback or product reviews into predefined groups.
Not ideal if you are looking for a state-of-the-art solution for complex text classification tasks, as its performance on the example dataset was noted to be less effective than an alternative method.
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Python
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Sep 10, 2021
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