giuseppebonaccorso/Reuters-21578-Classification
Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM
This project helps data scientists, machine learning engineers, and researchers classify news articles into predefined categories based on their content. You feed it a collection of text documents, like news headlines or full articles, and it outputs labels for each document, such as 'earnings', 'acquisitions', or 'crude'. It's designed for someone building or evaluating text classification models.
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Use this if you are a data scientist or researcher exploring traditional machine learning approaches for categorizing news or similar short texts.
Not ideal if you need a pre-built, out-of-the-box solution for production use without any coding or model development.
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Jupyter Notebook
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MIT
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Last pushed
Aug 08, 2017
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