sergio11/spam_email_classifier_lstm
This project uses a Bi-directional LSTM model π§π€ to classify emails as spam or legitimate, utilizing NLP techniques like tokenization, padding, and stopword removal. It aims to create an effective email classifier π»π while addressing overfitting with strategies like early stopping π«.
This project helps classify emails as either spam or legitimate based on their content. You feed it raw email text, and it tells you if the email is 'spam' or 'ham' (legitimate). This is useful for someone learning how deep learning and natural language processing can be applied to real-world text classification problems.
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Use this if you are a student or researcher exploring how to build an email spam filter using deep learning and natural language processing techniques.
Not ideal if you need a ready-to-deploy, robust email filtering solution for a production environment or commercial application.
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Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 21, 2025
Commits (30d)
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