A basic NLP classification task to classify between spam and ham on a given SMS spam dataset of 5,574 messages. The files contain one message per line. Each line is composed by two columns: v1 contains the label (ham or spam) and v2 contains the raw text. It has been deployed using streamlit and heroku.
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A basic NLP classification task to classify between spam and ham on a given Email spam dataset of 5,574 emails. The files contain one message per line. Each line is composed by two columns: v1 contains the label (ham or spam) and v2 contains the raw text.
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ashwinjohn3/Spam-Classifier
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A basic NLP classification task to classify between spam and ham on a given Email spam dataset of 5,574 emails. The files contain one message per line. Each line is composed by two columns: v1 contains the label (ham or spam) and v2 contains the raw text.
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