Shagun-25/Newsgroup_Classification_end_to_end
This is an end-to-end production-grade machine learning project using BERT Classifier, GitHub Actions, Flask Framework, Docker, and AWS Deployment.
This project helps classify news articles into one of 20 categories, such as 'rec.sport.baseball' or 'talk.politics.mideast'. You provide raw news article text, and it outputs the most likely newsgroup category for each article. This is useful for anyone who needs to automatically sort or organize large collections of text-based news content.
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Use this if you need to automatically categorize incoming news articles or other short text documents into predefined topics.
Not ideal if you need to classify documents into custom categories that are not part of the standard 20 newsgroup topics, or if you require sophisticated semantic search capabilities.
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Python
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Last pushed
Mar 16, 2024
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